Sequence gaps join mice and men: phylogenetic evidence from deletions in two proteins

Recent nuclear sequence analyses have provided evidence thatprimates and rodents are more closely related than previouslybelieved (Madsen et al. 2001 ; Murphy et al. 2001a, 2001b ).This proposal is difficult to reconcile with morphological insights(Liu et al. 2001 ; Novacek 2001 ) and is not generally supportedby current mitochondrial sequence data (Reyes, Pesole, and Saccone2000 ; Nikaido et al. 2001 ; Arnason et al. 2002 ; Janke etal. 2002 ). Moreover, the supporting data and analyses havebeen criticized on methodological grounds (Rosenberg and Kumar2001 ). Here we report deletions in two nuclear protein-codinggenes that lend independent support     

Using GEFs to deorphanize odorant receptors

Odorant perception is initiated when odorants activate uniquecombinations of odorant receptors (ORs) expressed in the ciliaof olfactory sensory neurons in the nose (Buck and Axel 1991;Malnic et al. 1999). One of the greatest challenges in the olfactoryscience is to correlate ORs with their ligands (to deorphanizethe ORs). The determination of OR–ligand pairs shouldreveal how the OR family is used to generate diverse odorantperceptions (Keller et al. 2007, Menashi et al. 2007). However,these studies are complicated     

Pharmacogenetic Analysis Reveals a Post-Developmental Role for Rac GTPases in Caenorhabditis elegans GABAergic Neurotransmission

The nerve-cell cytoskeleton is essential for the regulation of intrinsic neuronal activity. For example, neuronal migration defects are associated with microtubule regulators, such as LIS1 and dynein, as well as with actin regulators, including Rac GTPases and integrins, and have been thought to underlie epileptic seizures in patients with cortical malformations. However, it is plausible that post-developmental functions of specific cytoskeletal regulators contribute to the more transient nature of aberrant neuronal activity and could be masked by developmental anomalies. Accordingly, our previous results have illuminated functional roles, distinct from developmental contributions, for Caenorhabditis elegans orthologs of LIS1 and dynein in GABAergic synaptic vesicle transport. Here, we report that C. elegans with function-altering mutations in canonical Rac GTPase-signaling-pathway members demonstrated a robust behavioral response to a GABA_A receptor antagonist, pentylenetetrazole. Rac mutants also exhibited hypersensitivity to an acetylcholinesterase inhibitor, aldicarb, uncovering deficiencies in inhibitory neurotransmission. RNA interference targeting Rac hypomorphs revealed synergistic interactions between the dynein motor complex and some, but not all, members of Rac-signaling pathways. These genetic interactions are consistent with putative Rac-dependent regulation of actin and microtubule networks and suggest that some cytoskeletal regulators cooperate to uniquely govern neuronal synchrony through dynein-mediated GABAergic vesicle transport in C. elegans.EPILEPSY affects 1–2% of the world population and is associated with imbalances between excitatory and inhibitory neurotransmission in the brain (Locke et al. 2009). In particular, interneurons expressing gamma-aminobutyric acid (GABA), the principal inhibitory neurotransmitter in the human brain, are essential for normal neuronal synchronization and maintenance of a seizure threshold in humans (Cossette et al. 2002), rodents (Delorey et al. 1998), and zebrafish (Baraban et al. 2005). A failure of the brain to properly regulate neuronal synchrony can result from ion channel defects (Xu and Clancy 2008), neuropeptide depletion (Brill et al. 2006), brain malformations (Patel et al. 2004), interneuron loss (Cobos et al. 2005), and/or synaptic vesicle recycling failure (Di Paolo et al. 2002), all of which may be caused by disrupting the nerve-cell cytoskeleton. Therefore, further exploration of putative links between cytoskeletal components and neurotransmission may accelerate development of novel therapeutics for epilepsy.Epilepsy associated with cytoskeletal dysfunction often has a developmental basis (Di Cunto et al. 2000; Wenzel et al. 2001; Keays et al. 2007). For example, mutations in LIS1, a dynein motor complex regulator, lead to classical lissencephaly, which is characterized by neuronal migration defects, a lack of convolutions in the brain, mental retardation, and epileptic seizures (Lo Nigro et al. 1997). Yet, observations that lissencephaly-associated seizures worsen after neuronal migration ceases, while LIS1 expression persists, imply that LIS1 also acts in the adult brain (Cardoso et al. 2002).We previously reported that C. elegans with a predicted null mutation (t1550) in lis-1, the worm ortholog of human LIS1, exhibited synaptic vesicle misaccumulations, but not neuronal migration or axon-pathfinding defects, in GABAergic motor neurons. We also observed anterior “epileptic-like” convulsions, which were intense, frequent, and repetitive, with lis-1(t1550) homozygotes in the presence of pentylenetetrazole (PTZ; Williams et al. 2004), an epileptogenic GABA_A receptor antagonist (Huang et al. 2001; Fernandez et al. 2007). PTZ sensitivity was also increased in heterozygous lis-1(t1550) mutants following RNA interference (RNAi) against worm orthologs of associated cortical malformation genes, such as cdk-5 and nud-2, which are known to interact with LIS1 and the dynein motor complex. Depletion of these gene products was coincident with dynein-mediated synaptic vesicle transport defects, not with architectural defects, in GABAergic motor neurons (Locke et al. 2006).Plausible functional interactions among LIS-1, dynein, and Rac GTPases (Rehberg et al. 2005; Kholmanskikh et al. 2006) have not been explored in an intact adult nervous system. C. elegans is ideal for characterizing these interactions due to the availability of weak and strong Rac pathway mutants (Lundquist et al. 2001; Poinat et al. 2002; Lucanic et al. 2006), a comprehensive RNAi library (Kamath et al. 2003), and GFP-based neuronal markers. Here, we combine these tools with pharmacological modifiers of neuronal activity and establish an experimental paradigm that reveals a novel regulatory pathway. This pathway is composed of integrins at the plasma membrane that signal through Racs to dynein-associated proteins, which function to coordinate synaptic vesicle transport in larval and adult GABAergic motor neurons.     

Removal of Heavy Metals from Sewage Sludge Used as Soil Fertilizer

This work has examined sewage sludge of the following heavy metal concentrations (mg/kg): Cd-3.43; Co-5.25; Cu-131; Fe-51300; Mn-177; Ni-37.5; Pb-104; Zn-3300. Metals speciation by sequential extraction according to Tessier et al. (1979), and Rudd et al. (1988), and a procedure recommended by European Community Bureau of Reference (BCR) (Ure et al., 1993; Quevauiller et al., 1996; Davidson et al., 1999), as well as analysis of chemical forms of metals, have been carried out. It has been found that only Zn concentration is higher than the value permissible for agricultural sewage sludge application (2500 mg/kg). The results obtained by Tessier et al. (1979) Tessier, A., Campbell, P. C. and Bisson, M. 1979. Sequential extraction procedure for the speciation of particulate trace metals.. Anal. Chem., 51: 844–851. [Crossref], [Web of Science ®] [Google Scholar], and BCR procedures (Ure et al., 1993; Quevauiller et al., 1996; Davidson et al., 1999) appeared to be consistent. A comparison of the sequential analysis and the analysis of chemical forms of metals indicates that the sum of metal concentrations for the exchangeable, carbonate and bound to Fe/Mn oxyhydroxides forms (found by Tessier et al., 1979, and BCR analyses (Ure et al., 1993; Quevauiller et al., 1996; Davidson, et al., 1999)) corresponds to the sum of sulfate, oxide, metallic and siliceous forms. The concentrations of the forms bound to organic matter or sulfides correspond to the sulfide form while the residue corresponds to the ferrate form. Preparative extraction of metals from the sewage sludge using sodium salt of ethylenediaminetetraacetic acid (EDTA-Na), sodium pyrophosphate (V) and ammonia water has also been investigated. As far as the examined leaching agents are concerned, EDTA-Na appeared to be the best. Single leaching with this agent results in the following metal concentrations remaining in the sludge (mg/kg): Cd-1.1; Co-2.1; Cu-105; Fe-17700; Mn-28.3; Ni-12.8; Pb-44; Zn-1200. They meet the requirements of Polish regulations concerning the use of sewage sludge as a soil fertilizer.     

Chloroplast DNA in Mature and Senescing Leaves: A Reappraisal

The fate of plastid DNA (ptDNA) during leaf development has become a matter of contention. Reports on little change in ptDNA copy number per cell contrast with claims of complete or nearly complete DNA loss already in mature leaves. We employed high-resolution fluorescence microscopy, transmission electron microscopy, semithin sectioning of leaf tissue, and real-time quantitative PCR to study structural and quantitative aspects of ptDNA during leaf development in four higher plant species (Arabidopsis thaliana, sugar beet [Beta vulgaris], tobacco [Nicotiana tabacum], and maize [Zea mays]) for which controversial findings have been reported. Our data demonstrate the retention of substantial amounts of ptDNA in mesophyll cells until leaf necrosis. In ageing and senescent leaves of Arabidopsis, tobacco, and maize, ptDNA amounts remain largely unchanged and nucleoids visible, in spite of marked structural changes during chloroplast-to-gerontoplast transition. This excludes the possibility that ptDNA degradation triggers senescence. In senescent sugar beet leaves, reduction of ptDNA per cell to ∼30% was observed reflecting primarily a decrease in plastid number per cell rather than a decline in DNA per organelle, as reported previously. Our findings are at variance with reports claiming loss of ptDNA at or after leaf maturation.In vascular plants, copy numbers of plastid genomes (plastomes) frequently range from <100 per cell in meristematic cells to several thousand per cell in fully developed diploid leaf parenchyma cells. Microscopy studies have shown that the multicopy organelle genomes are usually condensed in more or less distinct DNA regions (nucleoids) within the organelle matrix or stroma.During development, the ratio of nuclear to organelle genomes appears to be relatively stringently regulated (Herrmann and Possingham, 1980; Rauwolf et al., 2010). Disregarding greatly varying absolute values (summarized in Rauwolf et al., 2010; Liere and Börner, 2013), there is little dispute that the number of plastid genomes and nucleoids per organelle and cell increase during early leaf development in higher plants (Kowallik and Herrmann, 1972; Selldén and Leech, 1981; Baumgartner et al., 1989; Fujie et al., 1994; Li et al., 2006; Rauwolf et al., 2010). This increase is usually accompanied by an increase in both size and number of plastids per cell (Butterfass, 1979). By contrast, data about plastid DNA (ptDNA) amounts in chloroplasts and cells of mature, ageing, and senescent tissue differ and are highly controversial. Basically two patterns have been described: the maintenance of more or less constant amounts of ptDNA per cell and/or organelle (Li et al., 2006; Zoschke et al., 2007; Rauwolf et al., 2010; Udy et al., 2012) or a significant decrease in copy number brought about by either continued organelle and cell division without ptDNA replication (Lamppa and Bendich, 1979; Scott and Possingham, 1980; Tymms et al., 1983) or by ptDNA degradation (Baumgartner et al., 1989; Sodmergen et al., 1991). In a series of communications, Bendich and coworkers recently reported that ptDNA levels decline drastically before leaf maturation in several plant species. In Arabidopsis thaliana and maize (Zea mays), ptDNA levels were reported to decrease early and precipitously as leaves mature. It was concluded that, in fully expanded leaves, most chloroplasts contain no or only insignificant amounts of DNA long before the onset of leaf senescence (Oldenburg and Bendich, 2004; Rowan et al., 2004; Oldenburg et al., 2006; Shaver et al., 2006; Rowan et al., 2009). Retention of ptDNA was proposed to be dispensable after the photosynthetic machinery was established in that the plastome-encoded photosynthesis genes were no longer needed in adult leaves. Degradation or even entire loss of ptDNA was considered as an event during plastid and leaf development, common to all plants (Rowan et al., 2009). ptDNA degradation was also suggested to act as a signal inducing senescence (Sodmergen et al., 1991).A priori, there is no reason why different ptDNA patterns should not occur, and there is indeed evidence that organelle DNA can behave differently in different materials, both quantitatively and structurally (e.g., Selldén and Leech, 1981; Baumgartner et al., 1989). However, since contradictory data were reported for the same species that were grown under comparable, if not identical, conditions (Rowan et al., 2004, 2009; Li et al., 2006; Oldenburg et al., 2006; Shaver et al., 2006; Zoschke et al., 2007; Evans et al., 2010; Udy et al., 2012), it is apparent that some of them must reflect methodological insufficiencies of the experimental approaches employed.From a physiological point of view, the existence of DNA-deficient plastids in photosynthetically competent tissue seems unlikely. For instance, due to its susceptibility to photooxidative damage, the D1 protein (PsbA), a plastome-encoded core subunit of photosystem II, must be replaced continuously by a complex repair system to maintain photosynthesis (Prasil et al., 1992). This replacement requires de novo synthesis of the short-lived D1. There are no data available supporting an extreme mRNA stability, protein stability, or for another compensating biochemistry, preserving organelle functions for weeks or even months. The maximum mRNA half-life reported for psbA is in the range of 40 h (Kim et al., 1993).Resolving this controversy is of considerable scientific interest, both from a theoretical and an applied perspective. We therefore analyzed the fate of ptDNA in mature, ageing, and senescent leaves of four commonly studied higher plant species (Arabidopsis, sugar beet [Beta vulgaris], tobacco [Nicotiana tabacum], and maize; Figure 1) for which conflicting data have been reported. Four complementary methods were used for assessing the presence of ptDNA as well as its quantitative and morphological changes during leaf development: an improved 4′,6-diamidino-2-phenylindole (DAPI)–based fluorescence microscopy approach including deconvolution of fluorescence images, electron microscopy, semithin sectioning across leaf laminas, and real-time quantitative PCR (see Methods).Open in a separate windowFigure 1.Developmental Leaf Series of Sugar Beet, Tobacco, and Arabidopsis.(A) Sugar beet leaves, developmental stages II to VI (left to right; see text). Inset: leaf stages y1 and y3. Arrows indicate necrotic areas. Bar = 5 cm.(B) Tobacco leaves, developmental stages II and IV to VI. Inset: leaf stages y1 and y2. Bar = 5 cm; bar in inset = 1 cm.(C) Arabidopsis plants (left) from which leaves of developmental stages I to VI were taken. Bar = 4 cm.Figure 2, Supplemental Methods, and Supplemental Data Sets 1 to 4 present representative micrographs of developmental series of DAPI-stained chloroplasts in leaf spongy parenchyma cells of late ontogenetic stages from sugar beet, Arabidopsis, tobacco, and maize displaying clearly discernible nucleoid patterns. Figures 1A to 1C document some of the leaves from which samples were taken. Mesophyll cells of juvenile leaves investigated in our previous work (Li et al., 2006; Zoschke et al., 2007; Rauwolf et al., 2010) were included for comparison (Supplemental Data Sets 1 to 4, panels 1 to 37, 84 to 94, 112 to 117, and 123 to 128). The staining specificity of the fluorochrome was confirmed enzymatically. Treatment with DNase, but not DNase-free RNase or Proteinase K, either before or after staining with the fluorochrome, abolished the fluorescence but did not significantly affect chloroplast structure (compare with Rauwolf et al., 2010; see Methods).Open in a separate windowFigure 2.DAPI-DNA Fluorescence of Mature, Senescent, and Prenecrotic Leaf Mesophyll Cells or Cell Segments.Representative DAPI-stained squashed mesophyll cells of sugar beet ([A] to [C]), Arabidopsis ([D] to [F]), tobacco ([G] and [H]), and maize ([I] and [J]) leaflets or leaves (cell detail in [C], [E], [F], and [H]) of the developmental stages III/IV (I), IV ([A] and [D]), V ([B], [E], and [G]), and VI ([C], [F], [H], and [J]). Note that (E) represents a cell fragment of Supplemental Data Set 2, panel 102. Bar = 5 μm in (A), also for (B) to (J).     

The contribution of αβ-tubulin curvature to microtubule dynamics

Microtubules are dynamic polymers of αβ-tubulin that form diverse cellular structures, such as the mitotic spindle for cell division, the backbone of neurons, and axonemes. To control the architecture of microtubule networks, microtubule-associated proteins (MAPs) and motor proteins regulate microtubule growth, shrinkage, and the transitions between these states. Recent evidence shows that many MAPs exert their effects by selectively binding to distinct conformations of polymerized or unpolymerized αβ-tubulin. The ability of αβ-tubulin to adopt distinct conformations contributes to the intrinsic polymerization dynamics of microtubules. αβ-Tubulin conformation is a fundamental property that MAPs monitor and control to build proper microtubule networks.Microtubules are polar polymers formed from αβ-tubulin heterodimers. These tubulin subunits associate head-to-tail to form protofilaments, and typically 13 protofilaments are associated side-by-side to form the hollow cylindrical microtubule. Most microtubules emanate from microtubule organizing centers, in which their minus ends are embedded. GTP-tubulin associates with the fast-growing plus ends as the microtubules radiate to explore the cell interior (see Box).

The cycle of microtubule polymerization.

Fig. 1). The addition of a new subunit completes the active site for GTP hydrolysis, and consequently most of the body of the microtubule contains GDP-bound αβ-tubulin. The GDP lattice is unstable but protected from depolymerization by a stabilizing “GTP cap,” an extended region of newly added GTP- or GDP.Pi-bound αβ-tubulin. The precise nature of the microtubule end structure and the size and composition of the cap are a matter of debate. Loss of the stabilizing cap leads to rapid depolymerization, which is characterized by an apparent peeling of protofilaments. “Catastrophe” denotes the switch from growth to shrinkage, and “rescue” denotes the switch from shrinkage to growth.Open in a separate windowFigure 1.Three structures of GTP-bound αβ-tubulin adopt similar curved conformations. Different αβ-tubulin structures were superimposed using α-tubulin as a reference, and oligomers were generated by assuming that the spatial relationship between α- and β-tubulin within a heterodimer is identical to the relationship between heterodimers. Curvature is calculated from the rotational component of the transformation required to superimpose the α-tubulin chain onto the β-tubulin chain of the same heterodimer. All of the GTP-bound structures (Rb3 complex, Protein Data Bank [PDB] accession no. 3RYH [magenta]; DARPin complex, PDB accession no. 4DRX [green]; TOG1 complex, PDB accession no. 4FFB [blue]) show between 10° and 13° of curvature, which is very similar to the curvature observed in GDP-bound structures (see inset, where the αβ-tubulins from a GDP-bound stathmin complex [PDB accession no. 1SA0] are shown in yellow and orange). A straight protofilament (putty and dark red color, PDB accession no. 1JFF) and a partially straightened assembly (tan) from GMPCPP ribbons are shown for reference.Unlike actin filaments, which grow steadily, microtubules frequently switch between phases of growth and shrinkage. This hallmark property of microtubules, known as “dynamic instability” (Mitchison and Kirschner, 1984), allows the microtubule cytoskeleton to be remodeled rapidly over the course of the cell cycle. “Catastrophes” are GTPase-dependent transitions from growing to shrinking, whereas “rescues” are transitions from shrinking to growing. Numerous microtubule-associated proteins (MAPs) regulate microtubule polymerization dynamics. Discovering how cells regulate and harness dynamic instability is a fundamental challenge in cell biology.A recent accumulation of structural, biochemical, and in vitro reconstitution data has advanced the understanding of dynamic instability and the MAPs that control it. Fresh structural data have provided insight into the process of microtubule assembly and defined how some MAPs recognize αβ-tubulin in and out of the microtubule. In vitro reconstitution experiments are reshaping the understanding of catastrophe and also providing quantitative insight into the mechanism of MAPs. Here, we review this progress, paying special attention to the emerging theme of interactions that are selective for different conformations of αβ-tubulin, both inside and outside the microtubule lattice. We argue for the central importance of recognizing these distinct conformations in the control of microtubule dynamics by MAPs and hence in the construction of a functional microtubule cytoskeleton by cells.

Tubulin dimers and their curvatures

It was clear in early EM studies that αβ-tubulin could form a diversity of polymers (Kirschner et al., 1974). In particular, the first cryo-EM of dynamic microtubules (Mandelkow et al., 1991) revealed significant differences in the appearance of growing and shrinking microtubule ends. Growing microtubule ends had straight protofilaments and were tapered, with uneven protofilament lengths, whereas shrinking microtubule ends had curved protofilaments that peeled outward and lost their lateral contacts. These and other data established the canonical model that GTP-tubulin is “straight” but GDP-tubulin is “curved” (Melki et al., 1989). The idea that GTP binding straightened αβ-tubulin into a microtubule-compatible conformation before polymerization was appealing because it provided a structural rationale for why microtubule assembly required GTP and how GTP hydrolysis could lead to catastrophe. A subsequent cryo-EM study (Chrétien et al., 1995), however, revealed that growing microtubules often tapered and curved gently outward without losing their lateral contacts. These data suggested that GTP-tubulin might not be fully straight at the time of its incorporation into the microtubule lattice, an observation that set the stage for a still-active debate on the structure of GTP-tubulin and of microtubule ends.The atomic details of “straight” and “curved” became apparent when the first structures of αβ-tubulin were solved. The straight conformation of αβ-tubulin was determined from cryo-electron crystallographic studies of Zn-induced αβ-tubulin sheets (Nogales et al., 1998). The structure showed linear head-to-tail stacking of αβ-tubulin along the protofilament, both within and between αβ-tubulin heterodimers. The curved conformation of αβ-tubulin was determined from x-ray crystallographic studies of a complex between αβ-tubulin and Rb3 (Gigant et al., 2000; Ravelli et al., 2004), a microtubule-destabilizing factor in the Op18/stathmin family (Belmont and Mitchison, 1996). In this complex, the individual α- and β-tubulin chains adopted a characteristic conformation distinct from their straight one. Longitudinal interactions also differed from those in the straight conformation (Fig. 1): within and between the heterodimers, successive α- and β-tubulin chains were related by an ∼12° rotation. A chain of these curved αβ-tubulins generates an arc with a radius of curvature resembling that of the peeling protofilaments at shrinking microtubule ends (Gigant et al., 2000; Steinmetz et al., 2000).Straight and curved are not the only two conformations, however. A cryo-EM study of αβ-tubulin helical ribbons trapped using guanylyl 5′-α,β-methylenediphosphonate (GMPCPP), a slowly hydrolyzable analogue of GTP, provided a molecular view of a possible microtubule assembly intermediate (Wang and Nogales, 2005). In these ribbons, GMPCPP-bound αβ-tubulin adopted a conformation roughly halfway (∼5° rotation) between the straight and curved conformations. These partially curved αβ-tubulin heterodimers formed two types of lateral bonds, only one of which resembled those in the microtubule. This structure suggested that at least some αβ-tubulin straightening occurs during polymerization.Until recently, structural information about the conformation of unpolymerized GTP-bound αβ-tubulin was notably lacking. Three recent crystal structures (Nawrotek et al., 2011; Ayaz et al., 2012; Pecqueur et al., 2012) have now provided remarkably similar views of this previously elusive species. In all three structures, GTP-bound αβ-tubulin adopts a fully curved conformation, with its α- and β-tubulin subunits related by ∼12° of rotation (Fig. 1). This curvature is not consistent with models in which GTP binding straightens unpolymerized αβ-tubulin. In each of the structures, αβ-tubulin is bound to another protein, stathmin/Rb3 (Ozon et al., 1997), a designed ankyrin repeat protein (DARPin; Pecqueur et al., 2012), as well as a TOG domain from the Stu2/XMAP215 family of microtubule polymerases (Gard and Kirschner, 1987; Wang and Huffaker, 1997). Biochemical experiments have failed to detect GTP-induced straightening of αβ-tubulin, arguing against the possibility that these unrelated binding partners forced GTP-tubulin to adopt the curved conformation. For example, the affinity of stathmin–tubulin interactions is the same for GTP-tubulin and GDP-tubulin (Honnappa et al., 2003). Similarly, five small molecule ligands that target the colchicine binding site and are predicted to bind only curved αβ-tubulin have equivalent affinity for GTP-tubulin, GDP-tubulin, and αβ-tubulin in the stathmin complex (Barbier et al., 2010). Likewise, a TOG domain from Stu2p binds to GTP- and GDP-tubulin with comparable affinity (Ayaz et al., 2012). Finally, DARPin binds equally well to GTP- and GDP-tubulin even though it contacts a structural element that is positioned differently in the straight and curved conformations (Pecqueur et al., 2012). Taken together with early biochemical experiments (Manuel Andreu et al., 1989; Shearwin et al., 1994), these new data strongly support a model in which unpolymerized αβ-tubulin is curved whether it is bound to GTP or to GDP (Buey et al., 2006; Rice et al., 2008; Nawrotek et al., 2011). According to this model, the curved-to-straight transition occurs during the polymerization process, not before. We discuss some implications of this new view at the end of the following section.

Conformation and dynamic instability

How does GTP hydrolysis destabilize the microtubule lattice and trigger catastrophe? A recent structural study has compared high-resolution cryo-EM reconstructions of GMPCPP microtubules and GDP microtubules to provide some answers to this question (Alushin et al., 2014). The structures show that GTP hydrolysis induces a compaction at the longitudinal interface between dimers, immediately above the exchangeable nucleotide-binding site. This compaction is accompanied by conformational changes in α-tubulin. In contrast, lateral contacts between tubulins were essentially unchanged in the different nucleotide states. These observations suggest that GTP hydrolysis introduces strain into the lattice, but how this strain affects the strength of longitudinal and lateral bonds to destabilize the microtubule remains unknown. The GMPCPP and GDP microtubules also show distinct arrangements of elements that bind to MAPs, which suggests a structural mechanism some MAPs could use to distinguish GTP lattices from GDP lattices (discussed later).In parallel with these structural advances, in vitro reconstitutions (Gardner et al., 2011b) have undermined the textbook view about the kinetics of catastrophe. The seminal measurements of catastrophe frequency (Walker et al., 1988, 1991) assumed that catastrophe occurred with the same probability on newly formed and old microtubules. In other words, the analysis implied that catastrophe was a first-order, single-step process. Although subsequent experiments (e.g., Odde et al., 1995; Janson et al., 2003) indicated that catastrophe involved multiple steps, the first-order view of catastrophe was widely adopted (Howard, 2001; Phillips et al., 2008). Recent experiments using a single-molecule assay for microtubule growth (Gell et al., 2010) have now shown definitively that catastrophe is not a single-step process; rather, newly formed microtubules undergo catastrophe less frequently than older ones (Gardner et al., 2011b). “Age-dependent” catastrophe implies that the stabilizing structure at the end of growing microtubules is evolving to become less effective. The timescale of this evolution is long compared with the kinetics of αβ-tubulin association (Gardner et al., 2011a). Thus, the ageing process probably reports on one or more structural properties of the microtubule end, such as the presence of “defects” in the lattice (Gardner et al., 2011b) or possibly increased tapering of microtubule ends (Coombes et al., 2013).It now seems clear that changes in the curvature of αβ-tubulin during microtubule polymerization are fundamental to microtubule dynamics and the regulatory activities of MAPs. Having straight conformations of αβ-tubulin only occur appreciably in the microtubule lattice provides a simple structural mechanism by which MAPs can discriminate unpolymerized from polymerized αβ-tubulin. Biochemical properties that define microtubule dynamics, like the strength of lateral and longitudinal contacts and the rate of GTP hydrolysis, may differ for curved, straight, and intermediate conformations of αβ-tubulin; e.g., curved forms probably bind microtubule ends less tightly than straight forms. By regulating when and where these different conformations occur, MAPs can tune microtubule dynamics. More speculatively, the complex biochemistry associated with different conformations of αβ-tubulin may contribute to the aging of microtubule ends, which leads to catastrophe. Understanding the connections between αβ-tubulin conformation, biochemistry, and polymerization dynamics is a major challenge for the future. Expanding the current mathematical models (Bowne-Anderson et al., 2013) and computational models (VanBuren et al., 2005; Margolin et al., 2012) of microtubule dynamics to incorporate these new findings about αβ-tubulin structure and age-dependent catastrophe may yield significant insights. In the following sections, we will examine recent studies that demonstrate how MAPs use selective interactions with distinct conformations of αβ-tubulin to control microtubule dynamics and thereby the physiology of the microtubule cytoskeleton.

Microtubule depolymerases stabilize curved conformations of tubulin

Perhaps the first direct evidence that MAPs might control the conformation of αβ-tubulin came from studies of microtubule depolymerases, which are proteins that promote, accelerate, or induce the depolymerization of microtubules (Howard and Hyman, 2007). Cells use microtubule depolymerases to maintain local control of microtubule catastrophe. Early electron microscopy studies of two unrelated depolymerases, Op18/stathmin and the kinesin-13 Xkcm1, showed that these proteins were able to induce/stabilize the curved conformation of αβ-tubulin and/or curved protofilaments (Desai et al., 1999; Gigant et al., 2000; Steinmetz et al., 2000). Depolymerases are also referred to as “catastrophe factors” because they trigger catastrophes in dynamic microtubules. The localized control of catastrophe is the essential function of depolymerases in cell physiology.The microtubule depolymerase stathmin is inactivated around chromosomes and at the leading edge of migrating cells (Niethammer et al., 2004), creating a gradient of depolymerase activity in these zones. Proteins in the Op18/stathmin family form a tight complex with two curved tubulin dimers (Fig. 2 A). Op18/stathmin proteins have been critical for the crystallization of tubulin (Ravelli et al., 2004; Gigant et al., 2005; Prota et al., 2013) and for biochemical studies of tubulin conformation. Although stathmins are frequently described as tubulin-sequestering proteins, the effect they have on microtubule catastrophe frequencies in vitro is much stronger than would be predicted from the simple sequestration of tubulin (Belmont and Mitchison, 1996). The potency of stathmins suggests that they induce catastrophes through direct interactions with microtubule ends, presumably weakening the bonds of terminal subunits by inducing or stabilizing their curvature (Gupta et al., 2013).Open in a separate windowFigure 2.Proteins that recognize curved αβ-tubulin tend to make long interfaces that span both α- and β-tubulin. (A) A stathmin family protein (blue) forms a long helix that binds two αβ-tubulin heterodimers (pink and green; PDB accession no. 3RYH). (B) The structure of a complex between kinesin-1 and αβ-tubulin (PDB accession no. 4HNA) is shown with the motor in dark green and αβ-tubulin in pink and lime. Depolymerizing kinesins have insertions (red segments modeled based on a crystal structure of MCAK; PDB accession no. 1V8K), such as the KVD finger, that expand the contact region compared with purely motile kinesins. (C) The TOG1 domain (blue) from Stu2, an XMAP215 family polymerase, contacts regions of α- and β-tubulin (pink and green) that move relative to each other in the curved (left, PDB accession no. 4FFB) and straight (right, model substituting straight αβ-tubulin; PDB accession no. 1JFF) conformations of αβ-tubulin. The asterisks show where this relative movement would disrupt the TOG–tubulin interface. Red side chains indicate conserved tubulin-binding residues at the top and bottom of the TOG domain. (D) The TOG2 domain from human CLASP1 (light blue, PDB accession no. 4K92) shows an “arched” interface that in docked models like the ones shown here is not complementary to curved (left) or straight (right) conformations of αβ-tubulin. Curved and straight structures are PDB 4FFB and 1JFF, respectively. Red side chains indicate binding residues similar to those in the polymerase family TOG domains, and asterisks highlight where the arched nature of this TOG prevents a conserved binding residue from contacting its interaction partner on β-tubulin.Kinesin-13s, first identified by their central motor domain (Aizawa et al., 1992; Wordeman and Mitchison, 1995), depolymerize microtubules catalytically using the energy of ATP hydrolysis (Hunter et al., 2003). Kinesin-13s depolymerize microtubules at spindle poles to generate poleward flux (Ganem et al., 2005), at kinetochores to drive anaphase chromosome segregation (Maney et al., 1998; Rogers et al., 2004), and in neuronal processes (Homma et al., 2003). Evidence that kinesin-13s depolymerized microtubules came from the discovery of the Xenopus laevis homologue, Xkcm1, in a screen for kinesin-related proteins involved in spindle assembly (Walczak et al., 1996). Incubation of Xkcm1, also known as MCAK, with GMPCPP microtubules caused peeled protofilaments and significant “ram’s horns” structures to appear at microtubule ends (Desai et al., 1999), which indicates that MCAK binds more tightly to curved structures than to straight ones. As with all kinesins, tight binding of the motor domain is coupled to its ATP hydrolysis cycle. Kinesin-13s first bind the microtubule lattice with an on-rate constant that strongly influences its depolymerase activity (Cooper et al., 2010). Kinesin-13s then target the end of the microtubule via “lattice diffusion,” a random walk mediated by electrostatic interactions that occurs in the ADP state (Helenius et al., 2006). Exchange of ADP to ATP occurs at microtubule ends; in the ATP state, MCAK binds tightly to tubulin dimers and either induces or stabilizes their outward curvature and detachment from the microtubule lattice (Friel and Howard, 2011). The subsequent hydrolysis of ATP causes kinesin-13 to release its tubulin subunit, now detached from the lattice, and begin another cycle of depolymerization (Moores et al., 2002).A distinguishing feature of the kinesin-13 motor domain is an extension of loop L2, known as the KVD finger (Ogawa et al., 2004; Shipley et al., 2004), which protrudes from the motor domain toward the minus end of the microtubule (Fig. 2 B). Alanine substitution of the KVD motif inhibits depolymerase activity in cell-based assays (Ogawa et al., 2004) and in vitro (Shipley et al., 2004). A recent cryo-EM study showed that the kinesin-13 motor domain contacts curved tubulin on three distinct surfaces (Asenjo et al., 2013) that differ from the contact surfaces of kinesin-1 (Sindelar and Downing, 2010; Gigant et al., 2013). The location of the kinesin-13 contact surfaces could allow kinesin-13 to stabilize spontaneous curvature of tubulin dimers at either microtubule end. Alternatively, tight binding of the kinesin-13 motor domain could directly induce curvature in the tubulin dimer. In either case, by promoting curvature at the growing microtubule end, kinesin-13s weaken the association of terminal subunits and induce catastrophes.Kinesin-8s are motile depolymerases (Gupta et al., 2006; Varga et al., 2006) that establish the length of microtubules in the mitotic spindle (Goshima et al., 2005; Rizk et al., 2014), position the spindle (Gupta et al., 2006), and modulate the dynamics of kinetochore microtubules (Stumpff et al., 2008; Du et al., 2010). Unlike the nonmotile kinesin-13s, whose motor domain is fully specialized for depolymerization, kinesin-8 proteins walk to the microtubule end and remove tubulin upon arrival (Gupta et al., 2006; Varga et al., 2006). Although it is unclear if depolymerase activity is fully conserved (Du et al., 2010; Mayr et al., 2011), all kinesin-8s combine motility with a negative effect on microtubule growth. For Saccharomyces cerevisiae Kip3p, the combination of motility and depolymerase activity has a significant functional consequence: Kip3p depolymerizes longer microtubules faster than shorter ones (Varga et al., 2006). This length-dependent depolymerization can be explained by an “antenna model.” In this model, longer microtubules will accumulate more kinesin-8s, which then walk toward the microtubule end, forming length-dependent traffic jams in some cases (Leduc et al., 2012). Because the rate of depolymerization depends on the number of kinesin-8s that arrive at the microtubule end, longer microtubules will be depolymerized more quickly. The “antenna model” depends critically on the high processivity of kinesin-8, which is thought to result from an additional C-terminal microtubule-binding element (Mayr et al., 2011; Stumpff et al., 2011; Su et al., 2011; Weaver et al., 2011); the C terminus may also contribute to a recently described microtubule sliding activity in Kip3p (Su et al., 2013). Intriguingly, a single Kip3p appears to be insufficient to remove a tubulin dimer. Rather, a second Kip3p must arrive at the microtubule end to bump off the first one (Varga et al., 2009).There are less structural and mutagenesis data available to explain the unique ability of kinesin-8s to walk and depolymerize. It is also not clear that all kinesin-8s use the same cooperative mechanism described for Kip3p. Like kinesin-13, the motor domain of kinesin-8 has an extended loop L2. This loop is disordered in the available crystal structure, but has been observed to contact α-tubulin in a cryo-EM reconstruction (Peters et al., 2010). The kinesin-8 loop L2 lacks a KVD sequence, however, and systematic mutations of L2 have not yet determined its role in depolymerase activity. The extent to which kinesin-8s recognize/induce curvature at microtubule ends remains unresolved. Truncated kinesin-8 motor domains can create small peels at the ends of GMPCPP microtubules (Peters et al., 2010), which suggests that kinesin-8 can induce or stabilize curvature. The fact that two kinesin-8s are required to dissociate a tubulin subunit, however, indicates that single motors alone do not substantially weaken the bonds holding the terminal tubulin subunit. Perhaps kinesin-8s do not stabilize curved forms of αβ-tubulin as strongly as kinesin-13s do.Reconstitution of microtubule dynamics in vitro showed that the depolymerizing kinesins affect catastrophe in different ways (Gardner et al., 2011b): kinesin-13s eliminate the aging process described earlier, whereas kinesin-8s accelerate it. Importantly, the local control of catastrophes by depolymerases is accomplished primarily through the local modulation of curvature at microtubule ends.

Growth-promoting MAPs also use conformation-selective interactions with αβ-tubulin

MAPs that accelerate growth or stabilize the microtubule lattice counteract microtubule depolymerases (Tournebize et al., 2000; Kinoshita et al., 2001). XMAP215 was discovered as the major protein in Xenopus extracts that promotes microtubule growth (Gard and Kirschner, 1987). Later, functional homologues were discovered in S. cerevisiae (Stu2p) (Wang and Huffaker, 1997) and other organisms (e.g., Charrasse et al., 1998; Cullen et al., 1999). XMAP215 family proteins localize to kinetochores and microtubule organizing centers, where they contribute to chromosome movements and to spindle assembly and flux (Wang and Huffaker, 1997; Cullen et al., 1999). Loss of XMAP215 family polymerase function leads to shorter, slower-growing microtubules and often gives rise to smaller and/or aberrant spindles (Wang and Huffaker, 1997; Cullen et al., 1999). All family members contain multiple TOG domains that bind αβ-tubulin (Al-Bassam et al., 2006; Slep and Vale, 2007). The molecular mechanisms underlying the activity of these proteins, and the collective action of their arrayed TOG domains, have until recently remained obscure. Recent progress is defining the structure and biochemistry of TOG domains and their interactions with αβ-tubulin. The emerging view is that XMAP215 family polymerases, like the depolymerases, bind to curved αβ-tubulin dimers as an important part of their biochemical cycle. In this section, we will focus on the most recent developments that are shaping the molecular understanding of growth-promoting MAPs, emphasizing the somewhat better studied XMAP215 family.Affinity chromatography using immobilized TOG domains from Stu2p revealed that the TOG1 domain binds directly to unpolymerized αβ-tubulin (Al-Bassam et al., 2006). TOG domains can also bind specifically to one end of the microtubule (Al-Bassam et al., 2006). Crystal structures of TOG domains, sequence conservation, and site-directed mutagenesis defined the αβ-tubulin–interacting surface, which forms a narrow “spine” of the book-shaped domain (Al-Bassam et al., 2007; Slep and Vale, 2007).In early models for XMAP215, the arrayed TOG domains were thought to bind multiple αβ-tubulins (Gard and Kirschner, 1987). Subsequent fluorescence-based reconstitution of XMAP215 activity, however, gave results that were not consistent with this “shuttle” model (Brouhard et al., 2008). The reconstitution assays showed that XMAP215 acted processively, residing at the microtubule end long enough to perform multiple rounds of αβ-tubulin addition. Intriguingly, XMAP215 increased the rate of, but not the apparent equilibrium constant for, microtubule elongation. XMAP215 also stimulated the rate of shrinkage in the absence of unpolymerized αβ-tubulin. Similar observations were made using Alp14 (Al-Bassam et al., 2012), a Schizosaccharomyces pombe XMAP215 homologue. These studies showed that XMAP215 catalyzes polymerization: it promotes microtubule growth by using its TOG domains to repeatedly bind and stabilize an intermediate state that otherwise limits the rate of polymerization.How do TOG domains recognize the microtubule end and promote elongation? Recent structural studies (Ayaz et al., 2012, 2014) suggest that interactions with curved αβ-tubulin play a central role. The crystal structures of complexes between αβ-tubulin and the TOG1 or TOG2 domains from Stu2p revealed that both TOG domains bind to curved αβ-tubulin (Ayaz et al., 2012, 2014; Fig. 2 C). The TOG domains do not interact strongly with microtubules even though the TOG-contacting epitopes are accessible on the microtubule surface (Ayaz et al., 2012). Preferential binding to curved αβ-tubulin (Ayaz et al., 2014) occurs because the arrangement of the TOG-contacting regions of α- and β-tubulin differs between curved and straight conformations (Fig. 2 C). Conformation-selective TOG–αβ-tubulin interactions explain how XMAP215 family proteins discriminate unpolymerized αβ-tubulin from αβ-tubulin in the body of the microtubule. XMAP215 family proteins require a basic region in addition to TOG domains for microtubule plus end association and polymerase activity (Widlund et al., 2011). The polarity of TOG–αβ-tubulin interactions and the ordering of domains in the protein together explain the plus end specificity of these polymerases: only at the plus end can TOGs engage curved αβ-tubulin while the C-terminal basic region contacts surfaces deeper in the microtubule (Ayaz et al., 2012). A recent study proposed that the linked TOG domains catalyze elongation using a tethering mechanism that effectively concentrates unpolymerized αβ-tubulin near curved subunits already bound at the microtubule end (Ayaz et al., 2014). The mechanisms by which these proteins catalyze depolymerization are less understood, although depolymerization can be explained by the catalytic stabilization of an intermediate state (Brouhard et al., 2008). By analogy with the depolymerases described earlier, the stabilization of such a state by arrayed TOG domains seems likely to also depend on the preferential interactions with curved αβ-tubulin.CLASP family proteins (Pasqualone and Huffaker, 1994; Akhmanova et al., 2001) also contain TOG domains, but they are used to different effect: CLASPs do not make microtubules grow faster but instead appear to regulate the frequencies of catastrophe and rescue. For example, in vitro reconstitutions using Cls1p, a CLASP protein from S. pombe, showed that Cls1p promoted rescue (Al-Bassam et al., 2010). CLASP family proteins also localize to kinetochores and contribute to spindle flux (Maiato et al., 2005). Loss of CLASP function affects microtubule stability and causes spindle defects (Akhmanova et al., 2001; Maiato et al., 2005), but does so without significantly affecting microtubule growth rates (Mimori-Kiyosue et al., 2006). CLASPs can also stabilize microtubule bundles/overlaps (Bratman and Chang, 2007). The recently published structure of a CLASP family TOG domain (Leano et al., 2013) provided an unexpected hint about a possible origin of the different activities. Indeed, the structure revealed significant differences with XMAP215 family TOG domains even though the CLASP TOG maintains evolutionarily conserved αβ-tubulin–interacting residues (Fig. 2 D). Whereas the αβ-tubulin binding surface of XMAP215 family TOGs is relatively flat, the equivalent surface of the CLASP TOG is arched in a way that appears to break the geometric match with curved αβ-tubulin (Leano et al., 2013; Fig. 2 D). This suggests that CLASP TOG domains might bind to an even more curved conformation of αβ-tubulin that has not yet been observed, that they do not simultaneously engage α- and β-tubulin, or that they do something else. It is not yet clear how these different possibilities might contribute to the rescue-promoting activity of CLASPs. However, even though the biochemical and structural understanding of how CLASP TOGs interact with αβ-tubulin is less advanced than for XMAP215 family TOGs, the conservation of critical αβ-tubulin–interacting residues makes it seem likely that conformation-selective interactions with αβ-tubulin will play a prominent role.The modulation of microtubule dynamics by XMAP215/CLASP family proteins ensures proper microtubule function in both interphase and dividing cells. As for the depolymerases, specific interactions with curved αβ-tubulin likely underlie the different regulatory activities of XMAP215/CLASP family proteins.

Sensing conformation at lattice contacts

Thus far, we have described how microtubule polymerases and depolymerases bind selectively to curved conformations of the αβ-tubulin dimer. These interactions play a significant role in the movement of tubulin dimers into and out of the microtubule polymer. Once in the polymer, αβ-tubulin dimers make contacts with neighboring tubulins. Recently, three MAPs were shown to bind microtubules at lattice contacts: (1) the Ndc80 complex, a core kinetochore protein; (2) doublecortin (DCX), a neuronal MAP; and (3) EB1, the canonical end-binding protein. Here we will summarize recent progress demonstrating how these proteins recognize distinctive features of lattice contacts.The Ndc80 complex is a core component of the kinetochore–microtubule interface (Janke et al., 2001; Wigge and Kilmartin, 2001; McCleland et al., 2003), forming a “sleeve” that connects the outer kinetochore to microtubules of the mitotic spindle (Cheeseman et al., 2006; DeLuca et al., 2006). Loss of Ndc80 function leads to chromosome segregation errors in mitosis (McCleland et al., 2004; DeLuca et al., 2005). Ndc80 binds to microtubules at the longitudinal interface between α- and β-tubulin and extends outward toward the plus end at an ∼60° angle (Cheeseman et al., 2006; Wilson-Kubalek et al., 2008). Ndc80 binds to both the intradimer and interdimer interface and forms oligomeric arrays (Alushin et al., 2010). The binding of Ndc80 to this longitudinal lattice contact may confer a preference for straight rather than curved microtubule lattices, because the shape of the Ndc80 binding site is expected to change as a protofilament bends (Alushin et al., 2010; Fig. 3 A). Preferential binding to straight protofilaments might allow the Ndc80 complex to remain attached to the end of a shrinking microtubule. Indeed, reconstitutions of the Ndc80 complex interacting with dynamic microtubules show that the curved shrinking end acts as a “reflecting wall,” giving rise to “biased diffusion” (Powers et al., 2009). Interestingly, the Ndc80 complex also promotes rescue (Umbreit et al., 2012), and selective binding to straight lattice contacts may contribute to this rescue activity.Open in a separate windowFigure 3.Proteins that bind microtubules can distinguish unique configurations at lattice contacts. (A) Ndc80 (light and dark blue) binds the contact within (dark blue) and between (light blue) αβ-tubulin heterodimers (pink and green). The left shows part of an Ndc80 array on straight protofilaments (PDB accession no. 3IZ0). The right shows that neighboring Ndc80 molecules clash when modeled onto a curved protofilament. Individual Ndc80s may read the conformation at a single joint, or the change in conformation may disrupt cooperative interactions between adjacent Ndc80s. (B) Two views of DCX (blue) binding a lattice contact at the vertex of four αβ-tubulins, PDB accession no. 4ATU. Cooperative interactions on the microtubule allow DCX to discriminate between the subtle changes that accompany different protofilament numbers (11: orange, EMDataBank [EMD] accession no. 5191; 13: red, EMD accession no. 5193; 15: yellow, EMD accession no. 5195). (C) EB1 (left, dark blue) binds at the same vertex as DCX (PDB accession no. 4AB0), but EB1 binds preferentially to GTP vertices over GDP vertices, and is not sensitive to protofilament number. The same section of microtubule with EB1 removed (right) shows the location of nucleotide-dependent changes at the four-way vertex: helix H3 of β-tubulin (red patch at the lower right of the four-way junction), and the intermediate (Int.) domain of α-tubulin (yellow patch at the top left of the four-way junction). pfs, protofilaments.DCX, a MAP expressed in developing neurons (Francis et al., 1999; Gleeson et al., 1999) and mutated in cases of subcortical band heterotopia (des Portes et al., 1998; Gleeson et al., 1998), is unique in its ability to bind specifically to 13-protofilament microtubules over other protofilament numbers (Moores et al., 2004; Fig. 3 B). DCX contains two nonidentical, microtubule-binding “DC” domains (Taylor et al., 2000) that share a ubiquitin-like fold (Kim et al., 2003). A cryo-EM reconstruction showed that a single DC domain binds to microtubules at the vertex of four tubulin dimers in the so-called “B” lattice configuration (Fourniol et al., 2010). The DCX binding site is ideally situated to detect the subtle changes at lattice contacts that result from different protofilament numbers, which range from 11 to 16 for mammalian microtubules (Sui and Downing, 2010). Despite their ideal location, protofilament preference is not a property of single DCX molecules. Rather, it is cooperative interactions between neighboring DCX molecules that are sensitive to the spacing between protofilaments (Bechstedt and Brouhard, 2012). In vitro, this selectivity enables DCX to nucleate homogeneous, 13-protofilament microtubules (Moores et al., 2004). The function of DCX in developing neurons remains unclear, with models ranging from microtubule stabilization (Gleeson et al., 1999) to regulation of kinesin traffic (Liu et al., 2012).EB1, the canonical end-binding protein (Morrison et al., 1998), uses its calponin homology (CH) domain (Hayashi and Ikura, 2003) to bind the same lattice contact as DCX (Maurer et al., 2012). EB1 forms “comets” by binding rapidly and tightly to a distinct feature at the growing microtubule end but only weakly to the “mature” lattice (Bieling et al., 2007). Recent work has defined this distinctive feature as the nucleotide state. EB1 binds preferentially to microtubules built from GTP analogues (Zanic et al., 2009; Maurer et al., 2011). Combined with careful analysis of the size, shape, and dynamics of EB1 comets (Bieling et al., 2007), these results established that EB1 recognizes microtubule ends by binding specifically to the “GTP cap,” which is an extended region of the microtubule end that is enriched with GTP- and GDP-Pi-tubulin dimers. A recent cryo-EM reconstruction of the CH domain of Mal3 (the S. pombe EB1) bound to GTPγS microtubules provided a possible structural mechanism for how EB1 might differentiate GTP from GDP lattices (Maurer et al., 2012; Fig. 3 C). Mal3 was observed to contact helix H3 of β-tubulin, which connects directly to the exchangeable nucleotide-binding site. EB1 also contacts the regions of α-tubulin that move during the compaction of the lattice that follows GTP hydrolysis (Alushin et al., 2014). Mutation of conserved EB1 residues that contact either helix H3 or the compacting region of α-tubulin disrupts the end-tracking behavior of EB1 (Slep and Vale, 2007; Maurer et al., 2012). Interactions with helix H3 and the compacting region of α-tubulin also enable EB1 to accelerate the transitions of tubulin from the GTP state to the GDP state; in other words, EB1 acts as a “maturation factor” for the microtubule end (Maurer et al., 2014). EB1 recruits a large network of plus-end-tracking proteins (Akhmanova and Steinmetz, 2008) through interactions with the EB1 C terminus (Hayashi et al., 2005; Honnappa et al., 2006) and EB1 homology domain (Honnappa et al., 2009). This diverse and complex protein network is essential for the regulation of microtubule dynamics, the capture of microtubule ends by the cell cortex (Kodama et al., 2003) and endoplasmic reticulum (Grigoriev et al., 2008), and the positioning of the mitotic spindle (Liakopoulos et al., 2003).As mentioned earlier, microtubule ends also show unique structural configurations, namely tapered, outwardly flared, and flattened structures collectively described as “sheets” (Chrétien et al., 1995). The sheets contain distinctive lattice contacts, and recent work shows that the microtubule-binding activities of DCX and EB1 are sensitive to these structural features. DCX, for example, binds specifically to the outwardly flared sheets (Bechstedt et al., 2014), which enables DCX to track microtubule ends. Evidence for the ability of EB1 to recognize or control a distinct lattice configuration comes from the reconstitutions showing that EB1 promotes elongation synergistically with XMAP215 (Zanic et al., 2013): lack of a detectable direct EB1–XMAP215 interaction suggested that the observed synergy was mediated through alterations of the microtubule end structure itself. Further evidence that EB1 can affect the structure of the microtubule lattice comes from data showing that EB1 can nucleate “A” lattice microtubules in vitro (des Georges et al., 2008) and influence protofilament number distributions (Vitre et al., 2008; Maurer et al., 2012). The connection between the structure of microtubule ends, their nucleotide state, and microtubule dynamics is an important open question.

Conclusions and outlook

The αβ-tubulin dimer adopts a range of conformations as it moves in and out of the microtubule polymer, including changes to its intrinsic curvature and changes to its lattice contacts. These different conformations affect microtubule dynamics by altering the strength of lattice association and the rate of GTP hydrolysis. The work we discussed here has revealed an intimate linkage between these different conformations and the activities of key proteins that regulate microtubule dynamics. It is now clear that selective interactions with distinct conformations of unpolymerized and polymerized αβ-tubulin define the cell physiology of the microtubule cytoskeleton. Recently developed methods for purifying or overexpressing αβ-tubulin (des Georges et al., 2008; Johnson et al., 2011; Widlund et al., 2012; Minoura et al., 2013) are facilitating structural studies and allowing the biochemistry of αβ-tubulin polymerization to be dissected in unprecedented detail. Microtubule structural biology is entering a golden age, where the pace of new structural information is accelerating. We anticipate that future crystallographic and high-resolution cryo-EM studies will define the strategies used by other MAPs to recognize and control the conformation of αβ-tubulin, and may reveal new conformations of αβ-tubulin inside and outside of the microtubule. Reconstitutions of microtubule dynamics are rapidly increasing in complexity and are beginning to reveal how the activities of multiple MAPs can reinforce or antagonize each other (Zanic et al., 2013). More complex reconstitutions are also defining the minimal requirements for creating cellular-scale structures like the mitotic spindle (Bieling et al., 2010; Subramanian et al., 2013). Reconstitutions will also greatly advance the understanding of the dynamics and regulation of microtubule minus ends. As the ever-advancing structural data are integrated with reconstitution data, incorporated into computational models, and correlated with cell biology experiments, a robust, multiscale understanding of microtubule biology will come within reach.     

ARHGEF17 sets the timer for retention of Mps1 at kinetochores

The kinetochore-associated kinase Mps1 controls the spindle assembly checkpoint, but the regulation of its kinetochore recruitment and activity is unclear. In this issue, Isokane et al. (2016. J. Cell Biol. http://dx.doi.org/10.1083/jcb.201408089) show that interaction with and phosphorylation of its substrate, ARHGEF17, regulates Mps1 kinetochore retention, suggesting an autoregulated, timer-like mechanism.To achieve mitotic fidelity, an elaborate mechanism called the spindle assembly checkpoint (SAC) has evolved to ensure proper chromosome–spindle attachment and alignment before anaphase. Through the action of many proteins found on centromeres and kinetochores, the SAC inhibits the anaphase promoting complex/cyclosome (APC/C) to prevent mitotic exit. The SAC must be highly tunable to rapidly respond to even a single misaligned chromosome, yet still allow mitosis to proceed in a timely manner once any alignment defects have been corrected. Mps1, a dual specificity kinase, is a core SAC protein that regulates kinetochore recruitment of other SAC proteins, including the protein kinases Bub1 and BubR1 and the APC/C inhibitor Mad2 (Maciejowski et al., 2010). Previous studies have implicated Mps1 dimerization and autoactivation (Hewitt et al., 2010; Jelluma et al., 2010), as well as the kinetochore component Ndc80/Hec1 and the Aurora B protein kinase, in targeting Mps1 to kinetochores (Saurin et al., 2011; Nijenhuis et al., 2013). The regulation of this targeting is less well understood, as are the mechanisms that ensure Mps1 is removed from kinetochores in a timely fashion. In this issue, Isokane et al. add ARHGEF17 to the list of Mps1 targeting machinery and propose that it mediates a timing mechanism that limits the duration of Mps1 activity at kinetochores.Isokane et al. (2016) became interested in ARHGEF17 after they uncovered this gene in the MitoCheck genome-wide RNAi screen for mitotic regulators (Neumann et al., 2010), but MitoCheck lacked the temporal resolution to determine the mitotic function of ARHGEF17. Using high-resolution confocal live-cell imaging, Isokane et al. (2016) showed that ARHGEF17-depleted HeLa cells exhibited accelerated mitoses with chromosome congression, biorientation, and segregation defects and performed phenotypic rescue using a mouse ARHGEF17 transgene. Consistent with a SAC function, Isokane et al. (2016) found that mitosis in ARHGEF17-depleted cells was not arrested in response to the microtubule poison nocodazole and that kinetochore localization of several core SAC proteins was deficient, including Bub1, BubR1, and Mad2 (Hewitt et al., 2010; Jelluma et al., 2010; Maciejowski et al., 2010). These functions of ARHGEF17 are conferred by its central Rho GEF domain (Rümenapp et al., 2002), which Isokane et al. (2016) found to be both necessary and sufficient for SAC activity. However, the SAC functions of ARHGEF17 are independent of its GEF activity, as the inactive mutant ARHGEF17^Y1216A (Zheng, 2001; Rümenapp et al., 2002) fully rescued the mitotic phenotypes.Because ARHGEF17 depletion phenocopied Mps1 inhibition, Isokane et al. (2016) explored a connection between the two and found that Mps1 interacts with the ARHGEF17 central domain and phosphorylates ARHGEF17 at three sites. Fluorescence cross-correlation spectroscopy (Wachsmuth et al., 2015) suggested that ARHGEF17 preferentially binds to inactive Mps1 in the cytoplasm, forming a complex required for localization of Mps1 and phosphorylation of its substrate, KNL1, at kinetochores (Yamagishi et al., 2012). ARHGEF17 localized to kinetochores independently of Mps1, but its only function in the SAC appears to be delivering Mps1 to kinetochores, as a kinetochore-tethered Mps1–CENP-B fusion bypassed the requirement for ARHGEF17 in the SAC. Interestingly, retention of the Mps1–ARHGEF17 complex at kinetochores is negatively regulated by Mps1 itself. The Mps1 inhibitor reversine increased recovery times for both Mps1 and ARHGEF17 in fluorescence recovery after photobleaching assays, indicating that Mps1 activity promotes their release from kinetochores. Based on these observations, Isokane et al. (2016) suggest an exciting model in which ARHGEF17 binding acts as a timer for retention of Mps1 at kinetochores: inactive Mps1 must form a complex with ARHGEF17 to bind to unattached/unaligned kinetochores, but once activated Mps1 limits its own retention at kinetochores by breaking apart the Mps1–ARHGEF17 complex (Fig. 1). Presumably, an individual molecule of Mps1 is retained at kinetochores for the time it takes it to phosphorylate the three sites on ARHGEF17 identified by Isokane et al. (2016).Open in a separate windowFigure 1.Proposed timer model for Mps1 retention at kinetochores. ARHGEF17 (red) binds inactive Mps1 (light blue) in the cytoplasm, and the complex binds to the outer kinetochore (gray) where Mps1 becomes activated (blue). Mps1 phosphorylates ARHGEF17 (blue circles), causing dissociation of both from kinetochores. It is still unknown where and how Mps1 is activated upon ARHGEF17 binding or where ARHGEF17 dissociates from Mps1 (blue question marks), and if and how Mps1 is inactivated or ARHGEF17 is dephosphorylated upon returning to the cytoplasm.This model will be very intriguing to the SAC field because it suggests a mechanism by which kinetochores achieve the proper amount of Mps1 at individual kinetochores to properly respond to chromosome alignment defects in a timely fashion. However, data presented in this study will have to be put into the context of other studies showing requirements for Ndc80/Hec1 and Aurora B in recruiting Mps1 to the kinetochore (Martin-Lluesma et al., 2002; Saurin et al., 2011; Nijenhuis et al., 2013; Zhu et al., 2013). Although Isokane et al. (2016) show that ARHGEF17 depletion has no effect on Ndc80 or Aurora B and demonstrate that its effect on Mps1 targeting is direct, how ARHGEF17 cooperates with Ndc80 and Aurora B remains to be determined. Perhaps, like Mps1, ARHGEF17 binds to Ndc80 and/or is regulated by Aurora B or perhaps Mps1 and ARHGEF17 cooperate by binding to different kinetochore components. The proposed timer model raises several exciting questions. The authors speculate that ARHGEF17 binding might activate Mps1, but this is not yet tested. It will also be important to determine the fates of Mps1 and ARHGEF17 once released from kinetochores. Does Mps1 remain active to support functions in the cytoplasm, or is it inactivated to participate in further cycles of kinetochore targeting and SAC activity? Is ARHGEF17 dephosphorylated to participate in further cycles and, if so, what is the phosphatase? The exciting study by Isokane et al. (2016) is just the first step toward addressing how and where Mps1 activity is regulated to in turn ensure timely activation and silencing of the SAC.     

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.Plant bioinformatics faces the challenge of integrating information from the related “omics” fields to elucidate the functional relationship between genotype and observed phenotype (Edwards and Batley, 2004), known as the genotype-phenotype map (Houle et al., 2010). One of the main obstacles is our currently limited ability of systemic depiction and quantification of plant phenotypes, representing the so-called phenotyping bottleneck phenomenon (Furbank and Tester, 2011). To get a comprehensive genotype-phenotype map, more accurate and precise phenotyping strategies are required to empower high-resolution linkage mapping and genome-wide association studies in order to uncover underlying genetic variants associated with complex phenotypic traits, which aim to improve the efficiency, effectiveness, and economy of cultivars in plant breeding (Cobb et al., 2013). In the era of phenomics, automatic high-throughput phenotyping in a noninvasive manner is applied to identify and quantify plant phenotypic traits. Plants are bred in fully automated greenhouses under predefined environmental conditions with controlled temperature, watering, and humidity. To meet the demand of data access, exchange, and sharing, several phenomics-related projects in the context of several consortia have been launched, such as the International Plant Phenotyping Network (http://www.plantphenomics.com/), the European Plant Phenotyping Network (http://www.plant-phenotyping-network.eu/), and the German Plant Phenotyping Network (http://www.dppn.de/).Thanks to the development of new imaging and transport systems, various automated or semiautomated high-throughput plant phenotyping systems are being developed and used to examine plant function and performance under controlled conditions. PHENOPSIS (Granier et al., 2006) is one of the pioneering platforms that was developed to dissect genotype-environment effects on plant growth in Arabidopsis (Arabidopsis thaliana). GROWSCREEN (Walter et al., 2007; Biskup et al., 2009; Jansen et al., 2009; Nagel et al., 2012) was designed for rapid optical phenotyping of different plant species with respect to different biological aspects. Other systems in the context of high-throughput phenotyping include Phenodyn/Phenoarch (Sadok et al., 2007), TraitMill (Reuzeau et al., 2005; Reuzeau, 2007), Phenoscope (Tisné et al., 2013), RootReader3D (Clark et al., 2011), GROW Map (http://www.fz-juelich.de/ibg/ibg-2/EN/methods_jppc/methods_node.html), and LemnaTec Scanalyzer 3D. These developments enable the phenotyping of specific organs (e.g. leaf, root, and shoot) or of whole plants. Some of them are even used for three-dimensional plant analysis (Clark et al., 2011). Consequently, several specific software applications (a comprehensive list can be found at http://www.phenomics.cn/links.php), such as HYPOTrace (Wang et al., 2009), HTPheno (Hartmann et al., 2011), LAMINA (Bylesjö et al., 2008), PhenoPhyte (Green et al., 2012), Rosette Tracker (De Vylder et al., 2012), LeafAnalyser (Weight et al., 2008), RootNav (Pound et al., 2013), SmartGrain (Tanabata et al., 2012), and LemnaGrid, were designed to extract a wide range of measurements, such as height/length, width, shape, projected area, digital volume, compactness, relative growth rate, and colorimetric analysis.The huge amount of generated image data from various phenotyping systems requires appropriate data management as well as an appropriate analytical framework for data interpretation (Fiorani and Schurr, 2013). However, most of the developed image-analysis tools are designed for a specific task, for specific plant species, or are not freely available to the research community. They lack flexibility in terms of needed adaptations to meet new analysis requirements. For example, it would be desirable that a system could handle imaging data from different sources (either from fully automated high-throughput phenotyping systems or from setups where images are acquired manually), different imaging modalities (fluorescence, near-infrared, and thermal imaging), and/or different species (wheat [Triticum aestivum], barley [Hordeum vulgare], maize [Zea mays], and Arabidopsis).In this work, we present Integrated Analysis Platform (IAP), a scalable open-source framework, for high-throughput plant phenotyping data processing. IAP handles different image sources and helps to organize phenotypic data by retaining the metadata from the input in the result data set. In order to measure phenotypic traits in new or modified setups, users can easily create new analysis pipelines or modify the predefined ones. IAP provides various user-friendly interfaces at different system levels to meet the demands of users (e.g. software developers, bioinformaticians, and biologists) with different experiences in software programming.     

Structural basis of the super- and hyper-relaxed states of myosin II

Super-relaxation is a state of muscle thick filaments in which ATP turnover by myosin is much slower than that of myosin II in solution. This inhibited state, in equilibrium with a faster (relaxed) state, is ubiquitous and thought to be fundamental to muscle function, acting as a mechanism for switching off energy-consuming myosin motors when they are not being used. The structural basis of super-relaxation is usually taken to be a motif formed by myosin in which the two heads interact with each other and with the proximal tail forming an interacting-heads motif, which switches the heads off. However, recent studies show that even isolated myosin heads can exhibit this slow rate. Here, we review the role of head interactions in creating the super-relaxed state and show how increased numbers of interactions in thick filaments underlie the high levels of super-relaxation found in intact muscle. We suggest how a third, even more inhibited, state of myosin (a hyper-relaxed state) seen in certain species results from additional interactions involving the heads. We speculate on the relationship between animal lifestyle and level of super-relaxation in different species and on the mechanism of formation of the super-relaxed state. We also review how super-relaxed thick filaments are activated and how the super-relaxed state is modulated in healthy and diseased muscles.

The super-relaxed state of myosinAnimal life is characterized by the constant need for food, which provides the raw materials for making ATP used in the body’s energy-requiring processes. A substantial amount of energy is expended by skeletal muscle, which in humans amounts to 30–40% of body mass (Janssen et al., 2000). During contraction, ATP is rapidly consumed by the molecular motor, myosin II, as it pulls on actin filaments to produce force and movement. But ATP is also used at a significant basal rate even in the resting state. Producing ATP is costly for the cell, so there is a substantial evolutionary advantage to minimizing its waste. Animals have adapted to this requirement by evolving a mechanism that reduces the consumption of ATP to minimal levels in relaxed (RX) muscle. This mechanism is known as super-relaxation or the super-relaxed state (SRX).SRX is a biochemical state in which ATP turnover by a portion of the myosin heads in the RX state of muscle thick filaments is much slower (∼10 times) than that of myosin II molecules in solution (Stewart et al., 2010; Cooke, 2011; Nag and Trivedi, 2021). This inhibited state, in equilibrium with a faster (RX) state, was suggested by early studies showing that the metabolic rate of live, resting muscle was much less than that expected from the ATP turnover rate of purified myosin (Ferenczi et al., 1978) and similarly that ATPase activity of RX myofibrils was also lower than expected from isolated myosin (Myburgh et al., 1995). A slow rate of ATP turnover was later directly demonstrated in studies of skinned muscle fibers (Stewart et al., 2010). The single ATP turnover rate is typically measured as the rate of binding of fluorescent ATP (mantATP) to, or release from, myosin heads in solution or in skinned fiber bundles (Hooijman et al., 2011; McNamara et al., 2015); conceptually, because P_i release is rate limiting, the apparent rates of ATP binding and ADP release effectively reveal the overall ATP turnover rate. Experimental curves are generally interpreted in terms of two exponentials, one with a slow rate (SRX) and the other with a faster but still slow (RX) rate of ATP use (Cooke, 2011), although additional exponentials can sometimes be resolved (Hooijman et al., 2011; Naber et al., 2011).The SRX state is ubiquitous and thought to be fundamental to muscle function, acting as a mechanism for parking and switching off—like a car—energy-consuming myosin motors when they are not being used. It has been detected in all muscles where it has been studied: vertebrate (including human) and invertebrate, fast and slow skeletal, and cardiac muscle (Stewart et al., 2010; Cooke, 2011; Hooijman et al., 2011; Naber et al., 2011; McNamara et al., 2015; Phung et al., 2020). A highly inhibited rate of ATP turnover also characterizes the switched-off state of vertebrate smooth muscle and nonmuscle myosin II molecules (Cross et al., 1988). SRX plays a critical role in muscle energetics, conserving ATP in resting as well as contracting muscles and providing a reserve of myosin heads for enhanced contractility in cardiac muscles (Cooke, 2011; Hooijman et al., 2011; Brunello et al., 2020; Ma et al., 2021b).What are the key features of the SRX state?The SRX state has two main parameters: (1) the rate of ATP use (i.e., ATP turnover rate, often expressed as its inverse, the ATP turnover time) and (2) the fraction of molecules exhibiting this rate. Both parameters are essential to understanding the significance of SRX in the energy balance of muscle: myosin heads with a very slow rate would be of little consequence if not present in substantial numbers. The rate of ATP use has been attributed to the specific conformation of the myosin head, which can impede, or not, the release of the products of ATP hydrolysis (ADP and P_i; Anderson et al., 2018), and the fraction of heads with this rate in muscle appears to be related to the intra- and intermolecular interactions that the heads undergo in thick filaments, as discussed below.ATP turnover by myosin heads can vary by six orders of magnitude, depending on the muscle and its state of activity (Cooke, 2011; Naber et al., 2011). These fall into four main groups, which, on a logarithmic scale, differ internally by small amounts, but by an order of magnitude or more between groups (Fig. 1 A). The fastest use of ATP is in contracting muscle (rate ≈ 10 s⁻¹), where actin activates the release of hydrolysis products in a process coupled to the power stroke of the myosin head. The advantages of force and movement are paid for by a rapid consumption of ATP. RX heads use ATP at least 100 times more slowly: some at the RX rate, similar to that of purified myosin in solution (<0.1 s⁻¹), and others at an SRX rate, 10 times slower (Fig. 1, A and B). As might be predicted from the two parameters of the SRX, nature has evolved different ways of saving energy in this state: decreasing the ATP turnover rate, increasing the fraction with the low rate, or a combination of the two. These strategies appear adapted to the different systems in which they are found. The SRX rate typically occurs in 50% or more of the heads in a thick filament, the balance being RX heads (Cooke, 2011). In certain muscles, there is an even slower rate (10 times slower than SRX), which we refer to as “hyper-relaxed” (HRX), present together with SRX and RX heads (Naber et al., 2011).Open in a separate windowFigure 1.ATP turnover rates of myosin and proposed relation to head organization. (A) Logarithmic plot of rates, varying from very slow (hyper-relaxed), to slow (super-relaxed), to fast (disordered-relaxed), to very fast (actin-activated). (B) Expanded plot of relaxed rates and proposed relation to head configuration and interactions. The cartoons show the IHM as found in single molecules (upper) and thick filaments (lower); in filaments, only molecules in a single crown are shown. The colored ellipses are the interacting motor domains. The smaller, gray domains are the ELCs and RLCs, and the gray lines are the proximal region of the myosin tail (S2). Molecules with a sufficient length of S2 (25 heptads [25 hep]; ∼250 Å) form an IHM, while single heads and two-headed molecules with only two heptads of tail show no interactions. Molecules in filaments have SRX and DRX turnover rates similar to those of isolated molecules (25-heptad IHM; cf. vertebrate IHM) or more inhibited (HRX) rates. Heads turn over ATP at fast (F; noninteracting), slow (S; interacting), or very slow (VS; more interactions) rates. Slow (attached) FHs of the IHM can detach and sway out (red, double-headed arrows) and, while detached, can equilibrate between the slow and fast conformations, similar to S1 (blue, reversible arrows). The “tail” in tarantula and the uncolored IHM in scallop provide additional, intermolecular interactions leading to the very slow rate; this rate is also seen in 10S myosin through intramolecular interactions with segment 2 of its own tail. The different lengths of the bars in A correspond to the lengths in B, which are drawn to include the range of rates for HRX, SRX, and DRX; the key point is the close clustering of rates within these groups and the large gaps between them.What is the structural basis of the SRX state?The early finding that myosin filaments in muscle had a slower ATP turnover rate than myosin II molecules in solution led to the idea that interactions of heads possible in the polymer (e.g., with the thick filament backbone), but not in the monomer, inhibited their activity (Myburgh et al., 1995; Stewart et al., 2010; Cooke, 2011). The first study to unequivocally show head organization in a thick filament indeed revealed such interactions—of heads with the backbone, with each other within a molecule, and with each other between molecules (Woodhead et al., 2005). Of particular note was a folding back of the two heads onto the proximal part of the tail (subfragment 2 [S2]), with which they interacted, and intramolecular interaction between the heads through their motor domains. This structure became known as the “interacting-heads motif” (IHM; Fig. 1 B, dotted box; Fig. 2 B; Woodhead et al., 2005; Alamo et al., 2008). Such interaction between heads had first been seen in isolated myosin molecules (Wendt et al., 2001; Burgess et al., 2007) and was thought to inhibit their activity. The two heads were called “blocked” and “free” (BH and FH, respectively), referring to their actin-binding capability (Wendt et al., 2001). In this model, actin binding by the BH would be blocked by interaction of its actin-binding site with the FH. While the FH actin-binding site was exposed, movement of its converter domain, needed for ATP product release, would be inhibited by binding to the BH (Wendt et al., 2001). The overall result would be inhibition of activity of both heads, but by different mechanisms. Interaction of the folded-back heads with S2 would further inhibit the motions required for ATPase activity (Woodhead et al., 2005).Open in a separate windowFigure 2.Structural basis of SRX. (A) Proposed conformations of myosin heads (S1), in equilibrium with each other, underlying SRX (left, bent) and DRX (right, straight) ATP turnover rates (Anderson et al., 2018). MD, motor domain. (B) IHM of cardiac HMM showing BH and FH (based on Protein Data Bank accession no. 5TBY). Ellipses show regions of interaction between BH and FH motor domains (black ellipse), FH and S2 (black circle), and BH and S2 (white ellipse; interaction occurs on rear side of BH). (C) Thick filament (tarantula; EM Data Bank accession no. 1950) showing IHMs lying along four coaxial helices (three on front marked with arrows) creating intermolecular interactions (ellipses) between FH of one IHM and regulatory domain of IHM above. M-line would be at the top of the image. The reconstruction shows the average positions of the heads in the filament; however, the FHs are thought to be dynamic, leaving and returning to the IHM (Fig. 1 B; see text). Models in this figure were created with UCSF Chimera (Pettersen et al, 2004).The IHMs in RX thick filaments are organized in helical arrays, with intermolecular interactions of IHMs with each other along the helices as well as with the filament backbone (Woodhead et al., 2005; Zoghbi et al., 2008; Zhao et al., 2009; Pinto et al., 2012; Woodhead et al., 2013; Sulbarán et al., 2015). Helical ordering requires the closed conformation of the myosin heads (Xu et al., 2003; Zoghbi et al., 2004; Xu et al., 2009) and is thought to be a signature of the IHM. It can be disrupted in multiple ways (increased salt level, phosphorylation of the myosin regulatory light chains [RLCs], substitution of GTP or ADP for ATP, lowering of temperature), and this is accompanied by reduction of the SRX state in each case (Stewart et al., 2010; Cooke, 2011). Conversely, conditions that enhance the IHM, such as treatment with the myosin inhibitor blebbistatin (Zhao et al., 2008; Xu et al., 2009; Fusi et al., 2015), enhance the SRX (Wilson et al., 2014; Fusi et al., 2015). These correlations led to the view that IHMs in the ADP.Pi prepowerstroke state (Xu et al., 1999), organized in helices and bound to the core of the thick filament, may be the structural basis of the SRX state (Stewart et al., 2010; Cooke, 2011; Wilson et al., 2014; Fusi et al., 2015; Alamo et al., 2016).Despite this suggestive evidence, however, recent single ATP turnover measurements of myosin constructs have shown that slow turnover of ATP occurs not only in thick filaments but also, to a small extent (∼10–20% of molecules), in isolated myosin heads (S1; Anderson et al., 2018; Rohde et al., 2018; Gollapudi et al., 2021b; the earlier, steady-state solution ATPase observations were not capable of revealing these low rates). Thus, neither the filamentous form of myosin nor the IHM is required for the SRX rate of ATP turnover, as originally thought. It has been suggested, instead, that myosin heads in solution exist in an equilibrium between a strongly bent (“closed”) conformation (in which the lever arm is tilted more toward the prestroke direction similar to that in the IHM structure; 10–20% of molecules) and a more extended (“open”) structure (Anderson et al., 2018) and that inhibition of phosphate release and thus ATP turnover by the closed structure could account for the observation of a small level of SRX in S1 (Figs. 1 B and 2 A). If this is the case, what is the role of the IHM in SRX?Different degrees of SRX correlate with different levels of head organizationMyosin heads can exist in several structural forms: single heads, two-headed myosin molecules or constructs, and the polymeric myosin filaments found in muscle. Studies show that SRX increases (greater inhibition or greater number of inhibited molecules) as myosin heads are incorporated into more complex structures. As mentioned, ∼10–20% of isolated myosin heads in solution have a slow rate (SRX) and are thought to be in equilibrium with the balance of heads having a turnover rate similar to the conventionally measured ATPase (RX heads; Anderson et al., 2018; Rohde et al., 2018; Gollapudi et al., 2021b). When myosin heads are present in two-headed constructs containing 25 heptads of tail (∼250 Å; Figs. 1 B and 2 B) or full-length S2, similar SRX and RX rates are observed, but the fraction of SRX heads increases to ∼25–30% (at physiological ionic strength; Anderson et al., 2018; Rohde et al., 2018; Gollapudi et al., 2021b), suggesting that the presence of two heads and/or the tail stabilizes the SRX head structure. Importantly, if the tail is short (only two heptads; Fig. 1 B), the rates and fractions are similar to those of S1 (Anderson et al., 2018), demonstrating the importance of the tail in creating the SRX. Modeling and experiments show that 25 heptads (or more) of tail is long enough for molecules to form an IHM with folded-back, interacting FHs and BHs (Figs. 1 B and 2 B; Anderson et al., 2018). Head–head and head–tail interactions would stabilize the heads in their inhibited conformations (Fig. 2 B), consistent with the increase in SRX fraction. The two-heptad-long tail is too short for these interactions (Fig. 1 B), and the molecule does not show evidence of head interactions (Nag et al., 2017): the heads behave like isolated S1 in solution, with only ∼10% having the SRX rate (Fig. 1 B; Anderson et al., 2018). We conclude that the stabilizing interactions in the IHM involving the tail and the two heads increase the number of heads in the SRX conformation.Studies of whole muscle fibers (vertebrate fast skeletal) show that when myosin molecules are in native thick filaments in their helically ordered IHM conformations (Zoghbi et al., 2008; AL-Khayat et al., 2013), the RX and SRX rates are again similar to those of S1 (Fig. 1 B), but the fraction of SRX now reaches 60–75% (Stewart et al., 2010; Cooke, 2011). A similar, greatly increased fraction of SRX heads is found in slow skeletal and cardiac muscle fibers and myofibrils (Stewart et al., 2010; Hooijman et al., 2011; McNamara et al., 2017; Nelson et al., 2020; Gollapudi et al., 2021a). In filaments, IHMs undergo intermolecular interactions that cannot occur with single molecules (Zoghbi et al., 2008; AL-Khayat et al., 2013). These include interactions between heads of different IHMs along the myosin helices (Fig. 2 C), interaction of heads with tails in the filament backbone, and interaction with myosin-binding protein C (MyBP-C) and titin, lying on the filament surface (Nag et al., 2017). We suggest that these interactions further stabilize the FHs and BHs of the IHMs, without significantly affecting their conformation, leading to the high percentage of SRX in filaments (Anderson et al., 2018).These observations are consistent with the concept suggested earlier that the SRX rate is a consequence of a specific conformation of myosin heads, which inhibits ATP turnover, and with stabilization of this conformation by intra- and intermolecular interactions of the heads (Anderson et al., 2018). When heads are attached to each other in myosin constructs with a sufficient length of tail, forming the IHM, the inhibited conformation is stabilized by intramolecular interactions of the two heads with each other and with the myosin tail, approximately doubling (25–30%) the SRX fraction found in single heads (10–20%). When IHMs are incorporated into thick filaments, the inhibited heads are further stabilized by intermolecular interactions, with a further doubling of the SRX fraction to 60–75%. Thus, while the IHM is not a requirement for the SRX state, in real muscle, it strongly enhances it.Are the RX and SRX rates associated with specific heads in the IHM? It is known experimentally that the BH is more stably associated with the IHM than the FH. EM images of smooth muscle heavy meromyosin (HMM; a soluble, proteolytic fragment of myosin containing the two heads and the proximal third of the tail) show molecules where the BH is attached to S2 but the FH has dissociated (Burgess et al., 2007). This and studies of tarantula thick filaments (Brito et al., 2011; Sulbarán et al., 2013) suggest that the FH can dissociate from the IHM and become mobile (“swaying”; Fig. 1 B, red double-headed arrows), with a duty ratio that defines the fraction of time spent in the dissociated state (Alamo et al., 2017). When unconstrained in this way, the FH presumably acts essentially like S1 in solution, equilibrating between its minor SRX (bent) and its predominant RX (straight) rate of ATP turnover (Fig. 1 B, reversible blue arrows). Thus, the more stable BH would account for most of the SRX rate and the dissociated FH for the faster, RX rate. When the FH is docked in the IHM, stabilized in its inhibited form by interactions with the BH and S2 in the IHM, it may slow to approximately the BH SRX rate (Fig. 1 B; Alamo et al., 2016). The BH and docked FH may have similar enough rates that they are not resolved by the two-exponential analysis; there is in fact some evidence that additional exponentials give an improved fit (Hooijman et al., 2011), but this has not been explored in detail. The idea that some heads can move freely for a portion of the time, leading to their disordering in thick filaments, and the correlation of disorder with the RX rate, has led to the concept of the “disordered relaxed state” (DRX; Wilson et al., 2014). Thus, heads in thick filaments are typically referred to as SRX or DRX.What is the structural basis of the HRX state?Studies of invertebrate (tarantula) striated muscle show that the SRX state in some species can be enhanced by a further (10 times) slowing of the ATP turnover rate compared with the SRX (Fig. 1) and that this occurs in up to 50% of the heads (Naber et al., 2011). We refer to this as the HRX state. The HRX state has not been observed in vertebrate striated muscle thick filaments or myosin molecules. Is there a structural explanation for the greater inhibition of ATP turnover in tarantula muscle? The cryo-EM reconstruction of tarantula filaments shows that the IHMs in this species are arranged in four coaxial helices, with crowns of four IHMs spaced 145 Å apart axially (Woodhead et al., 2005). Each IHM shows the conventional structure of two heads interacting with each other through their motor domains and with the proximal portion of the myosin tail. Importantly, the reconstruction also suggests an additional key interaction that is apparently absent in vertebrate thick filaments (see below). S2, after leaving its IHM, travels along the filament toward the bare zone, passing near the next IHM along the filament axis, through a groove formed by the BH SRC homology 3 (SH3) and converter domains (Fig. 3 A; and Fig. 4, A and B; Woodhead et al., 2005). This location suggests that S2 could sterically interfere with movement of the BH converter region of this IHM that is required for product release. It could thus act as an additional constraint on the already inhibited conformation of the BH that further inhibits ATP turnover (each BH would thus interact with two S2s, its own and that from the axially adjacent IHM). In this case, we suggest that intermolecular interaction does not simply stabilize the inhibited head conformation but creates a new and additional physical barrier to motions of the BH required for ATPase activity, leading to the highly inhibited HRX turnover rate. The reconstruction shows that only the BHs are affected in this way, which could directly explain the finding that 50% of heads are in the HRX state (Naber et al., 2011).Open in a separate windowFigure 3.Comparison of intermolecular interactions in 3-D reconstructions of different thick filaments. Reconstructions are fitted with IHM atomic models (Protein Data Bank accession nos. 3JBH or 5TBY) in each case. All thick filaments (except insect flight muscle; Hu et al., 2016) show interactions between IHMs along the helical tracks (arrows), involving the FH motor domain at one level and the BH lever arm at the next. These interactions are the same at every level in tarantula and scallop (true helical structures) but different at different levels in vertebrates, which are quasi-helical. Additional interactions vary between species. (A) Tarantula shows interaction of S2 from one crown of heads with SH3 and converter domains of the next level (circles; see Fig. 4, A and B). IHM (Protein Data Bank accession no. 3JBH) was fitted to four levels of heads in cryo-EM reconstruction (EMD accession no. 1950; gray). (B) Similar fitting of IHM (Protein Data Bank accession no. 5TBY) to vertebrate (human) cardiac negative stain reconstruction of C-zone (EMD accession no. 2240) shows well-ordered IHMs at two of every three levels of heads (strong map density for pink and cyan IHMs), while the third level (yellow) is poorly ordered (weak map density, suggesting substantial IHM mobility; Zoghbi et al., 2008; AL-Khayat et al., 2013). S2 cannot be fitted unambiguously due to low resolution of map and lack of internal detail with negative stain; within these limitations, there is no obvious S2–head interaction between crowns (circles; see Video 1; cf. Video 2 for 3-D view). (C) In scallop cryo-EM reconstruction, S2 is not resolved, but the tight azimuthal crowding of IHMs around the circumference at each crown suggests potential intermolecular interaction between the SH3 domain of a BH and the motor domain of the neighboring FH (circles). Filaments are oriented with M-line at top; their different symmetries (fourfold, threefold, and sevenfold rotational symmetry, respectively) cause the varying views of the IHMs in the different filaments. All reconstructions are at the same scale. The human has a smaller diameter due to radial shrinkage occurring during negative staining and to the smaller number of molecules (n = 3) at each level. The scallop and tarantula cryo-reconstructions also have different diameters: scallop has seven molecules at each level forming a shell above the filament backbone (Woodhead et al., 2013), while tarantula has four molecules at each level, closer to the backbone (Woodhead et al., 2005), leading to a smaller diameter. Models in this figure were created with UCSF Chimera (Pettersen et al, 2004).Open in a separate windowFigure 4.Comparison of tail interactions with the SH3 and converter domains in atomic models of tarantula thick filaments and 10S smooth muscle myosin. (A and B) Tarantula thick filament (Protein Data Bank accession no. 3JBH). (C and D) 10S myosin (Protein Data Bank accession no. 6XE9). (A and C) Front views at same scale. (B and D) End views (same scale) obtained by rotating A and C 90° around the x axis so that pink IHM in A is closest to viewer (i.e., looking toward M-line). S2 in tarantula filament and segment 2 (Seg2) in 10S myosin both pass through a groove formed by the SH3 and converter (Cnv) domains of the BH motor domain (MD). The looser fit to the groove in tarantula may be due to the lower resolution of the reconstruction used to obtain the atomic model (20 Å resolution; cf. 4.3 Å for 10S myosin). Models in this figure were created with UCSF Chimera (Pettersen et al, 2004).Several observations support this structural interpretation of the HRX state. Vertebrate thick filaments have a symmetry and organization of myosin heads that is different from those in tarantula. Although no cryo-EM reconstruction of vertebrate filaments is available, two negative stain reconstructions of the C-zone (the middle section of each filament half, containing MyBP-C) clearly show the well-known quasi-helical arrangement of myosin heads characteristic of vertebrates (Zoghbi et al., 2008; AL-Khayat et al., 2013). Fitting of the IHM into the density map reveals well-ordered IHMs at two of every three levels of heads, while the third level is relatively disordered (Zoghbi et al., 2008; AL-Khayat et al., 2013). S2 cannot be fitted with certainty due to the low resolution of the map and ambiguities of negative stain; however, there is no obvious interaction of S2 from one crown with heads in the next (Fig. 3 B; Video 1; cf. Video 2). Correspondingly, vertebrate filaments do not exhibit an HRX state. There is also no HRX state in isolated S1- or S2-headed myosin constructs forming the IHM (Anderson et al., 2018; Rohde et al., 2018). These observations are consistent with the conclusion that in tarantula, intermolecular interaction with S2 from the neighboring crown is responsible for the HRX state. Note that the “ultra-relaxed” state induced in myosin by the inhibitor blebbistatin (Gollapudi et al., 2021a) has a very different origin from the HRX—the former due to internal stabilization of switch 2 in the myosin head in the closed state, inhibiting phosphate release (Zhao et al., 2008), the latter to the external structural constraints on head movements that we have described here.Video 1.Human cardiac thick filament reconstruction (EMD accession no. 2240) fitted with human cardiac atomic model (Protein Data Bank accession no. 5TBY) to show apparent absence of interaction between S2 from one level of heads and the SH3 and converter domains (red) of the next level. M-line at top. See also Fig. 3 B. Compare with Video 2.Video 2.Tarantula thick filament reconstruction (EMD accession no. 1950) fitted with tarantula IHM atomic model (Protein Data Bank accession no. 3JBH) to show 3-D view of interaction between S2 from one level of heads and the SH3 and converter domains (red) of the next level. M-line at top. See also Fig. 3 A and Fig. 4, A and B.Additional evidence comes from smooth muscle and nonmuscle myosin molecules, which can exist in a switched-off state in which the ATP turnover rate is similar to that in tarantula—also an HRX state (Cross et al., 1988). Strikingly, these myosins have a folded conformation, in which the two heads form an IHM, and the tail folds into three segments, the middle segment wrapping around the BH (Fig. 1 B; Suzuki et al., 1982; Trybus et al., 1982; Craig et al., 1983; Burgess et al., 2007; Yang et al., 2019). Cryo-EM analysis of this conformation shows intimate contact of the tail with the BH motor as it runs through the groove formed by the BH SH3 and converter domains (Fig. 4, C and D; Scarff et al., 2020; Yang et al., 2020). The regions of tail contact with the BH in these single molecules are very similar to those in the tarantula filament and would sterically impede BH converter movement, contributing to the HRX turnover rate of this inhibited form of the myosin molecule (Fig. 4). Although the inhibitory regions of the tail (S2 in tarantula, the middle segment of the tail in smooth muscle and nonmuscle myosin) and the nature of the interaction (intermolecular in one, intramolecular in the other) are both different, the likely inhibitory effects on BH converter movement and ATPase activity appear to be similar, supporting the importance of this interaction in generating the HRX state. HMM from these myosins lacks the distal two-thirds of the tail and therefore the interaction of the middle segment with the BH. Correspondingly, HMM exhibits an SRX but not an HRX rate (Cross et al., 1988). Together these observations provide strong support for the notion that interaction of the myosin tail with the SH3/converter region of the BH is the structural basis of hyper-relaxation.Another invertebrate muscle in which a putative HRX state has been observed is the scallop striated adductor. When thick filaments lose their ATP, helical ordering of the heads is lost (we would suggest by straightening of the heads in the apo state, so that the IHM can no longer form). EM shows that this process takes up to 30 min in scallop (Vibert and Craig, 1985), consistent with an HRX turnover rate. Scallop thick filaments differ from tarantula in having sevenfold rather than fourfold rotational symmetry (Vibert and Craig, 1983). Cryo-EM shows that this tightly packs the IHMs around the circumference of each crown, creating intermolecular interactions within crowns involving the SH3 domain of the BH and the motor domain of its neighbor FH (Figs. 1 B and 3 C; Woodhead et al., 2013; the heads in tarantula crowns are more widely spaced and do not show these interactions). While the reconstruction does not provide detail on possible tail interactions between crowns (as in tarantula), these additional intermolecular interactions may constrain the heads within a crown, impeding structural changes of the BH and FH and accounting for the hyper-slow release of products from scallop thick filaments through a mechanism quite different from that in tarantula.How is the IHM formed?Formation of the IHM depends on several key properties of myosin II: flexing of the heads and the head–tail junction and interaction of the motor domains with each other and with the proximal region of S2. BH–S2 interaction (where S2 runs over the bent BH) appears to be the primary binding interaction of the IHM (Alamo et al., 2016), as it is observed in smooth muscle HMM even when the FH is not bound to the BH (Burgess et al., 2007); FH–S2 interaction without interaction of the BH and BH–FH interaction without S2 are not observed. Interaction of S2 with the BH can only occur when the BH folds back onto the tail, and then only when the BH is in the strongly bent (Rosenfeld et al., 1994; Alamo et al., 2008, 2016; Scarff et al., 2020; Yang et al., 2020), nucleotide-trapping state, putatively with the SRX rate (Anderson et al., 2018). Thus, we picture the myosin molecule as having flexible heads (in a bent–straight equilibrium biased 90% toward the straight [DRX] conformation), which are flexibly attached to the tail, with the following sequence for formation of the IHM. If a transiently bent head comes in contact with S2, it binds and is stabilized in its bent (SRX) state, thereby becoming a BH (i.e., a precursor IHM; Alamo et al., 2016). The other head, flexing around its head–tail junction and in a similar bent–straight equilibrium, can now be caught (becoming an FH) when its converter region contacts the captured BH motor domain, stabilizing the FH bent conformation (Liu et al., 2003; Alamo et al., 2016; Scarff et al., 2020; Yang et al., 2020). This interaction is strengthened by contact of loops on the FH with S2 (Alamo et al., 2008; Scarff et al., 2020; Yang et al., 2020).Structural observations show that both heads of the IHM are strongly bent (Wendt et al., 2001; Woodhead et al., 2005; Scarff et al., 2020; Yang et al., 2020), while the bent structure in isolated heads may be uncommon. The sequence proposed above suggests how the IHM can be formed despite these constraints. If the bent structure occurs only rarely (e.g., 10% of the time), the likelihood of two bent heads coming together will be low: this likelihood is greatly increased by initial stabilization of one bent head (the BH) binding to S2 (forming the precursor IHM) and then binding of the second head (the FH) to the already bent BH of the precursor. This kinetic argument would explain why head–head interaction without involvement of the tail has not been observed, consistent with mutational studies (Adhikari et al., 2019). The final IHM is a tripartite structure with multiple weak interactions (BH–FH, BH–S2, and FH–S2) that inhibit ATPase activity as well as actin-binding capability (Scarff et al., 2020; Yang et al., 2020). These interactions are easily broken and in equilibrium with the noninteracting form. The result in isolated sarcomeric myosin soluble fragments at physiological ionic strength is an overall 25% SRX and 75% DRX rate (Anderson et al., 2018; Rohde et al., 2018; Gollapudi et al., 2021b). In filaments, individual IHMs (with the inhibited, bent structure of the individual heads) are stabilized by intermolecular interactions occurring in the polymer (as described earlier), increasing the fraction of SRX heads above 50%.Is there a relationship of the SRX state with animal lifestyle?We have suggested that nature uses two ways to enhance the SRX state: increase in fraction of inhibited heads and increase in degree of inhibition. The particular mechanism may be adapted to the lifestyle of the animal (Naber et al., 2011). Tarantulas spend long periods of time immobile and can survive many months without food. Minimizing ATP use during this time by hyper-relaxation of their BHs and SRX of most of their FHs would be an evolutionary advantage (Naber et al., 2011). They would nevertheless be ready for a rapid switch to the active state through the small numbers of swaying FHs that sense thin filament activation when muscle is stimulated (Brito et al., 2011). Scallops can swim quickly for short bursts by jet propulsion, using their striated adductor muscles to rapidly close their shell (e.g., to escape predators), but they remain stationary during extended periods of filter feeding (Speiser and Wilkens, 2016). In this low-activity state, the shell is held partially closed through contraction of the tonic smooth adductor muscle, which enters a catch state, maintaining force with little energy expenditure (Chantler, 2016). The striated adductor is 10 times more massive than its smooth counterpart (Naidu, 1987) and a potential metabolic drain during the long periods when the muscle is not in use: minimizing ATP use during these nonswimming periods through hyper-relaxation of their heads would be advantageous. The folded form of vertebrate smooth muscle and nonmuscle myosin is thought to serve as a storage molecule, which can be activated to form functional filaments as required through phosphorylation of their RLCs (Cross et al., 1988). The complete switching off of ATPase activity through hyper-relaxation when the molecule is not in use would again provide an evolutionary advantage.Vertebrate striated muscle thick filaments exhibit SRX but not hyper-relaxation. Interaction of IHMs with each other or with the filament backbone, MyBP-C, or titin enhances the fraction of heads in the SRX state but does not significantly increase the level of inhibition of the heads. SRX appears to be developed most strongly in the C-zone (probably in the two crowns of heads showing IHMs in each three-crown repeat), implicating MyBP-C in this inhibition (McNamara et al., 2016, 2019; Nelson et al., 2020). Myosin heads in the D-zone and in the non-IHM crown in the C-zone are less ordered (Zoghbi et al., 2008; AL-Khayat et al., 2013; Brunello et al., 2020) and may be the main source of DRX heads detected by single turnover experiments (Nelson et al., 2020). Vertebrates may make a trade-off of greater (though still low) ATP use in the RX state (SRX with some DRX heads) for the ability to switch on instantly as needed and for fine-tuning of the contractile response through interactions with other proteins such as MyBP-C.How are thick filaments activated from the SRX state?We have painted a picture in which most myosin heads in the thick filaments of resting muscle are tacked down on the filament surface in helices of IHMs in an SRX (or HRX) state. However, muscles must be ready for immediate activation from this energy-saving state. The other part of the picture therefore includes a small fraction of heads dissociated from the IHM at any particular moment. These relatively few, mobile, constitutively on (“sentinel”) heads are presumed to constantly explore the interfilament space, able to instantly sense thin filament activation and bind to actin when myosin-binding sites are exposed (by Ca²⁺-induced tropomyosin movement; Gordon et al., 2000), leading to initial tension development (Linari et al., 2015; Irving, 2017). We suggest that these are the transiently dissociated (swaying) FHs of the IHMs. In vertebrates, the sentinel heads could also include the less well-ordered heads at every third crown of the C-zone (Zoghbi et al., 2008; AL-Khayat et al., 2013) or the disordered heads in the D-zone (Brunello et al., 2020; Nelson et al., 2020). This essential role for a small number of mobile heads as the trigger for thick filament activity, when thin filaments are switched on, is paid for by the increase in ATP consumption over that used by SRX heads. What happens next depends on the type of muscle.In tarantula, the small amount of thick filament activity in an initial twitch appears to be enhanced in additional twitches by Ca²⁺-induced activation of myosin light chain kinase, which phosphorylates the FH RLCs, leading to increased release of the FHs from the IHMs, reduction in the HRX fraction and increase in the DRX fraction (Naber et al., 2011), and increased force production (Padrón et al., 2020). Prolonged high Ca²⁺ (e.g., in a tetanus) subsequently phosphorylates the BHs, resulting in their release and further enhancement of force (Padrón et al., 2020).Vertebrates have a finely tuned, graded response to activation. X-ray studies show that low-force isotonic contractions use only a small fraction of available heads (Linari et al., 2015). The majority remain helically ordered in their IHM configurations, continuing to save energy—even during contraction—representing a highly efficient use of ATP. As force increases, stress on the thick filaments rises, resulting in release of more heads, which produce greater force, in a positive feedback loop (Linari et al., 2015; Irving, 2017). In this mechanosensing model for thick filament activation, the filament is stretched by ∼1%, which may be sufficient to weaken intermolecular contacts between heads along the helical tracks that help to maintain the IHM conformations (Irving, 2017). Destabilization of the IHMs by stress could thus release the additional heads needed for strong force production. When contraction is switched off by removal of Ca²⁺ from the cytosol, IHMs rapidly go back to their helically ordered arrangement (Linari et al., 2015; cf. Ma et al., 2019), quickly returning the muscle to its energy-saving SRX state.In scallop, the thick filaments are directly activated by Ca²⁺ binding to the essential light chains (ELCs) on the myosin heads rather than through Ca²⁺ activation of the thin filaments (Szent-Györgyi et al., 1999; Chantler, 2016). Ca²⁺ binding causes breakage of the IHM intra- and intermolecular interactions, cooperatively releasing heads from their SRX/HRX state (Szent-Györgyi et al., 1999; Zhao and Craig, 2003; Jung et al., 2008; Chantler, 2016). Released Ca²⁺-activated heads can move freely, similarly to phosphorylated heads of tarantula, interacting with actin to generate force. As this process involves binding of Ca²⁺ to the myosin heads and not the slower, enzymatic phosphorylation of the light chains, full activation can occur rapidly (Zhao and Craig, 2003), making all heads immediately available for the powerful twitches that produce the strong swimming motions of this species. In the absence of a thin filament switch in scallops, sentinel heads may not be required as the heads directly sense Ca²⁺ activation.Interactions between IHMs along their helical tracks are common to all thick filaments in the SRX/HRX state. Reconstructions of tarantula, scallop, and vertebrate thick filaments, representing three distinct mechanisms of activation, all show such interactions, typically between the FH motor domain of one IHM and the BH regulatory domain of its neighbor in the next crown closer to the filament center (Figs. 2 C and ​and3;3; Woodhead et al., 2005; Zoghbi et al., 2008; AL-Khayat et al., 2013; Woodhead et al., 2013). As described earlier, these intermolecular interactions appear to stabilize the IHM conformation, enhancing the fraction of SRX heads in filaments. Concomitantly, they may also underlie rapid thick filament activation, as they provide a direct physical path for cooperative disruption of the IHM and thus exit from the SRX state (Stewart et al., 2010; McNamara et al., 2015). Cooperative exit from the SRX state has been experimentally demonstrated in skeletal and cardiac muscle incubated with mantATP chased by ADP (Stewart et al., 2010; Cooke, 2011; Gollapudi et al., 2021b). Cooperative activation is especially well developed in scallop thick filaments (Szent-Györgyi et al., 1999; Chantler, 2016), where it may underlie the rapid Ca²⁺ activation leading to the strong swimming motions of this species. The intermolecular interactions along helices and around each crown in scallops (Fig. 3 C; Woodhead et al., 2013) connect all heads in an extensive network that could be rapidly disrupted by Ca²⁺ binding.How is SRX modulated?The stability of the IHM and the level of SRX can be modulated in several ways, including myosin RLC phosphorylation and, in vertebrates, phosphorylation of MyBP-C (Stewart et al., 2010; Nag and Trivedi, 2021). RLC phosphorylation in tarantula greatly reduces the fraction of SRX and HRX heads and their ATP turnover times (Naber et al., 2011) while increasing DRX heads. This correlates with a decrease in helical ordering and extension of heads from the filament backbone (suggesting disruption of the IHM), as demonstrated by x-ray diffraction (Padrón et al., 2020) and EM (Craig et al., 1987). Phosphorylation not only activates heads but also maintains a memory of activation following the extensive phosphorylation that occurs in a tetanus; this can greatly potentiate subsequent contraction (Padrón et al., 2020). Disruption of the IHM and extension of heads toward neighboring actin filaments in the RX period following a tetanus presumably enables the stronger and more rapid interaction with actin of a post-tetanic contraction (Padrón et al., 2020). While the phosphorylated RX state that follows a tetanus would temporarily consume more ATP, it could provide a survival benefit by enabling stronger contractions when escaping predators or capturing prey. Following such periods of activity, the RLCs again become dephosphorylated, and the energy-saving SRX/HRX state, with ordered, interconnected IHMs lying along the filament surface, returns (Padrón et al., 2020), characterizing the long periods of inactivity in the life of the tarantula, when ATP savings are critical.Vertebrate skeletal muscle RLCs can also be phosphorylated, and phosphorylation correlates with post-tetanic potentiation (Sweeney et al., 1993) together with disordering of myosin helices and extension of heads from the filament surface (Levine et al., 1996; Yamaguchi et al., 2016), again suggestive of IHM disruption. As with tarantula, a corresponding reduction in the SRX state with phosphorylation (Stewart et al., 2010; Cooke, 2011; Gollapudi et al., 2021b), with a temporarily greater resting ATP consumption, pays for the greater contractility available following phosphorylation.Vertebrates have a second means of modulating the SRX state, which may provide finer control of thick filament activation/relaxation than with invertebrates. MyBP-C binds to myosin in the middle one-third of each half of the thick filament (the C-zone; Craig and Offer, 1976; Flashman et al., 2004; Luther et al., 2008), and several lines of evidence demonstrate that the SRX state is more pronounced in these regions (McNamara et al., 2016, 2019; Nelson et al., 2020; Nag and Trivedi, 2021), reaching as high as 90% (Nelson et al., 2020); this correlates with the clearest delineation of IHMs in reconstructions of the thick filament C-zone (Zoghbi et al., 2008; AL-Khayat et al., 2013). Toward the tips of the filament (the distal or D-zone), heads are less ordered (Brunello et al., 2020; R. Craig, unpublished EM data), and the SRX state is diminished (Nelson et al., 2020). In MyBP-C knockout mice, the IHM configuration is weakened or abolished (Zoghbi et al., 2008), and the SRX state is disrupted (McNamara et al., 2016). Thus MyBP-C appears to enhance the SRX state, apparently by stabilizing the IHM. This stabilization is further modulated by phosphorylation of MyBP-C, occurring in the heart in response to β-adrenergic stimulation. Enhancement of cardiac contractility by cardiac MyBP-C (cMyBP-C) phosphorylation may result in part from depression of cMyBP-C’s stabilizing effect on the SRX, which coincides with weakening of the IHM (Kensler et al., 2017; Caremani et al., 2019b; Irving and Craig, 2019; McNamara et al., 2019). These data overall imply that MyBP-C enhances energy saving by stabilizing the IHM structure and that this is modulated in the heart by cMyBP-C phosphorylation (McNamara et al., 2019).Importantly, in the healthy heart, RLC and MyBP-C phosphorylation are not zero but ∼50% (Chang et al., 2015) and ∼60% of maximum (Previs et al., 2012), respectively. This would suggest a partial weakening of the SRX state (compared with zero phosphorylation) during normal cardiac activity, which may poise myosin heads optimally between sequestration in the IHM (to save energy) and availability for interaction with actin to generate force, with fine-tuning of these levels available upon further phosphorylation. Thus, we assume that the level of SRX of a muscle (degree of IHM formation) is tuned to the physiological needs of the moment, with the goal over time of minimizing energy consumption within these limits. Strikingly, phosphorylation levels of MyBP-C and RLC can both decrease in heart failure (El-Armouche et al., 2007; Toepfer et al., 2013), which would predict a higher fraction of SRX heads. This may reduce the need for energy under these adverse circumstances but may also contribute to the compromised contractility of the failing heart.Animals can save energy when food supplies are scarce or weather conditions adverse by a reduction in body temperature. This occurs naturally in ectotherms (cold-blooded animals) when exterior temperatures drop and by hibernation in some endotherms (warm-blooded animals), where body temperature and metabolism reduce to low values. Does enhanced SRX play a role in energy conservation under these circumstances? X-ray diffraction of both mammalian and tarantula muscle at low temperatures (10°C) suggests that the number of myosin motors in the helically ordered, IHM conformation decreases substantially compared with temperatures nearer physiological levels (Malinchik et al., 1997; Xu et al., 1997; Caremani et al., 2019a, 2021; Ma et al., 2021a); modeling of tarantula suggests that it is specifically the FHs that are disordered, while the BHs remain ordered (Ma et al., 2021a). This disordering suggests that the SRX state may actually be reduced, rather than enhanced, in cold temperatures. Other factors may contribute to energy conservation by muscle under cold conditions (Caremani et al., 2021; Ma et al., 2021a): myosin heads become refractory to actin binding at low temperature (Caremani et al., 2019a), and the disordered FHs, containing ADP.Pi at the active site, may transition toward the ATP conformation, inhibiting ATP turnover (Xu et al., 1999; Ma et al., 2021a). The impact of torpor (a form of hibernation) on the SRX state has recently been explicitly studied in the 13-lined ground squirrel (Ictidomys tridecemlineatus; Toepfer et al., 2020). During torpor, core body temperature drops to 5°C, metabolic rate to 3% of basal levels, and heart rate from 311 to 6 beats per min; hummingbirds undergo a similar dramatic reduction in metabolic rate to save energy each night (Shankar et al., 2020). The fraction of SRX heads found in cardiac muscle removed from the ground squirrel during torpor was reported to increase from 65 to 75%, contrary to expectation from the low-temperature x-ray studies of mammalian muscle described above that would imply a decrease in the number of IHMs. This discrepancy could be due to performance of the SRX measurements at 21°C (Toepfer et al., 2020) rather than the low temperatures used in the x-ray experiments that revealed helical disordering. The latter would presumably reflect the thick filament structure most accurately at actual torpor temperatures. We speculate that the phenomenon of iguanas (ectotherms) falling from trees and becoming immobile when environmental temperatures are abnormally low (Stroud et al., 2020) may be caused in part by the refractory impact of temperature on the ability of their myosin heads to bind to actin; a similar effect may have contributed to extinction of the dinosaurs during the global cooling that followed the asteroid impact of 66 million years ago (Vellekoop et al., 2014).Modulation of the SRX and its putative structural correlate, the IHM, may play a critical role in a number of cardiac diseases and their treatment, summarized elsewhere (Alamo et al., 2017; Nag et al., 2017; Yotti et al., 2019; Trivedi et al., 2020; Daniels et al., 2021; Schmid and Toepfer, 2021). Hypertrophic cardiomyopathy (HCM) is an inherited disease caused by mutations in sarcomeric proteins, including myosin, and characterized by hypercontractility and the inability to fully relax during diastole (Ashrafian et al., 2011). Recent studies show that mutations in the myosin heavy chain (MYH7; accounting for ∼40% of HCM cases) strongly cluster in regions of the myosin molecule involved in the interfaces of the IHM (Alamo et al., 2017; Nag et al., 2017), and lead to a substantial decrease in SRX and increased energy use (Anderson et al., 2018; Adhikari et al., 2019; Sarkar et al., 2020). Disruption of the IHM by such mutations, at the head–head or BH–S2 interface, could release more heads for interaction with actin, accounting for the hypercontractility and impaired relaxation observed (Alamo et al., 2017; Anderson et al., 2018; Spudich, 2019; Sarkar et al., 2020). Experimental evidence for this proposal has been obtained (Adhikari et al., 2019; Sarkar et al., 2020). Mutations in MyBP-C leading to HCM also appear to partially disrupt the SRX state of the myosin heads (Toepfer et al., 2019; Nag and Trivedi, 2021), leading to an increase in the number of DRX heads, which may contribute to the observed hypercontractility (McNamara et al., 2017). Depending on the mutation, cMyBP-C may have a reduced affinity for myosin, or the amount of MyBP-C incorporated into the thick filament may be reduced. It has been proposed that either mechanism would reduce the strength of the cMyBP-C–myosin interaction, releasing heads from the filament backbone (DRX heads), which could be partially responsible for the hypercontractile phenotype observed in patients with these mutations (Colson et al., 2007; Toepfer et al., 2019; Nag and Trivedi, 2021).Impaired relaxation due to HCM mutations in myosin (and other myofibrillar proteins) can be compensated by a recently developed drug, mavacamten, which has been shown to increase the fraction of myosin heads in the SRX state (Anderson et al., 2018; Rohde et al., 2018; Spudich, 2019; Nag and Trivedi, 2021), specifically in the D-zone of thick filaments (Nelson et al., 2020), concomitant with an increased number of molecules folded into the IHM conformation (Anderson et al., 2018; Rohde et al., 2018; Gollapudi et al., 2021b). In thick filaments of intact cardiac muscle, mavacamten increases the degree of quasi-helical ordering of myosin heads, consistent with an increase in the stability or fraction of molecules in the IHM conformation (Anderson et al., 2018), supporting our overall contention that the IHM is the main basis of the SRX state in muscle. Mavacamten inhibits the ATPase activity of isolated S1, specifically by inhibiting phosphate release (Green et al., 2016), suggesting that it enhances the bent (SRX) state of the myosin head, which, based on our earlier reasoning, would lead to the observed increase in the fraction of molecules in the IHM (Anderson et al., 2018).Future directionsWe currently know the structure of the IHM at ∼15 Å resolution in tarantula (Yang et al., 2016) and insect (Hu et al., 2016) filaments and ∼4 Å resolution in single smooth muscle myosin molecules (Scarff et al., 2020; Yang et al., 2020). Improvements in resolution should enhance visualization of the side-chain interactions that stabilize the SRX state in both filament and monomer. For filaments, cryo-EM of tarantula offers the greatest potential, owing to the stability of its helices. To better understand how mutations in the IHM interfaces lead to the hypercontractility of HCM, cryo-EM of vertebrate cardiac thick filaments is required to improve the resolution beyond the current ∼40 Å (obtained with negative staining; Zoghbi et al., 2008; AL-Khayat et al., 2013), a difficult task owing to the lability and quasi-helical symmetry of the vertebrate thick filament head array. Differences in the levels of SRX in the C- and D-zones of the thick filaments (Nelson et al., 2020) suggest differences in IHM stability or interactions, which will need to be analyzed by cryo-EM, again a significant task for the reasons stated above and because of the small size of these zones. The most detailed insights into IHM intramolecular interactions should come from a high-resolution structure of the IHM in isolated cardiac myosin molecules, which is urgently needed. This could potentially be obtained by x-ray crystallography or cryo-EM of IHM constructs (e.g., 25 heptad; Fig. 1; Anderson et al., 2018), although this is likely to be hampered by the relative instability of the structure. Incubation with mavacamten may improve its stability (Anderson et al., 2018). How interaction of MyBP-C with myosin enhances the SRX state is another fertile but challenging area of investigation, which may require cryo-electron tomography of thick filaments or intact myofibrils (Burbaum et al., 2021) or single particle cryo-EM studies of MyBP-C–IHM complexes. Experiments suggest that thick filaments in muscle are in equilibrium with a pool of myosin monomer, which may play a role in thick filament assembly/disassembly during development, hypertrophy, and myosin turnover (Saad et al., 1986; Katoh et al., 1998; Ojima, 2019). Myosin monomers at physiological ionic strength form IHMs with a folded tail structure and slow ATP turnover rate, which may act as a transport form from ribosome to filament (Ankrett et al., 1991; Katoh et al., 1998; Jung et al., 2008). Whether the SRX/IHM structure in thick filaments affects the monomer–polymer equilibrium is an area for future investigation.ConclusionThe SRX state of thick filaments plays a crucial role in the energy balance of muscle and is ubiquitous across the animal kingdom. It results from a conformation of the myosin head in which ATP turnover is strongly inhibited, minimizing ATP use. This conformation is stabilized by intramolecular interactions when it is incorporated into the IHM and by additional intermolecular interactions when IHMs are assembled into thick filaments, increasing the fraction of energy-saving SRX heads. Thus, we propose that IHMs, helically organized along the thick filament surface in the relaxed state, are the major basis of SRX in living muscle. An HRX state, found in thick filaments of some invertebrates and in the folded (storage) form of smooth muscle and nonmuscle myosin molecules, is also based on the IHM but in these cases results from additional intra/intermolecular interactions. A filament in which every head was in SRX, while maximally saving ATP, would not be useful in contraction: at any time, a small fraction of heads is dissociated (DRX or sentinel heads) and available to sense thin filament activation and generate initial force. The SRX state is down-regulated in situ by RLC and MyBP-C phosphorylation in response to physiological requirements (activation), which disrupt the IHM, releasing heads for interaction with actin. Mutations in myosin or MyBP-C causing HCM disrupt the SRX state, causing hypercontractility, which can be reversed by drugs that stabilize the IHM and thus the SRX.Online supplemental materialVideo 1 shows human cardiac thick filament reconstruction fitted with a human cardiac atomic model to demonstrate an apparent absence of interaction between S2 from one level of heads and the SH3 and converter domains of the next level. Video 2 shows tarantula thick filament reconstruction fitted with a tarantula IHM atomic model to show that in this species there is an interaction between S2 from one level of heads and the SH3 and converter domains of the next level.     

ATG8ylation of proteins: A way to cope with cell stress?

The ATG8 family of proteins regulates autophagy in a variety of ways. Recently, ATG8s were demonstrated to conjugate directly to cellular proteins in a process termed “ATG8ylation,” which is amplified by mitochondrial damage and antagonized by ATG4 proteases. ATG8s may have an emerging role as small protein modifiers.

ATG8 proteins directly conjugate to cellular proteinsAutophagy describes the capture of intracellular material by autophagosomes and their delivery to lysosomes for destruction (Kaur and Debnath, 2015). This process homeostatically remodels the intracellular environment and is necessary for an organism to overcome starvation (Kaur and Debnath, 2015). The autophagy pathway is coordinated by autophagy-related (ATG) proteins that are controlled by diverse post-translational modifications (e.g., phosphorylation, acetylation, ubiquitination, and lipidation; Ichimura et al., 2000; McEwan and Dikic, 2011). Recently, a previously uncharacterized post-translational modification termed “ATG8ylation” was uncovered (Agrotis et al., 2019; Nguyen et al., 2021). ATG8ylation is the direct covalent attachment of the small ubiquitin-like family of ATG8 proteins to cellular proteins (Agrotis et al., 2019; Nguyen et al., 2021). Until now, the only known instances of ATG8 conjugation to proteins were of a transient nature, as E1- and E2-like intermediates with ATG7 and ATG3, respectively, as a way of ligating ATG8 to the lipid phosphatidylethanolamine during autophagy (Ichimura et al., 2000). Therefore, ATG8ylation may represent an underappreciated regulatory mechanism for many cellular proteins that coordinate pathways such as mitophagy.ATG8s play many roles in the autophagy pathwayDuring canonical autophagy, the ATG8 family (comprising LC3A, -B, and -C and GABARAP, -L1, and -L2) undergoes molecular processing that concludes with their attachment to phosphatidylethanolamine, enabling proper construction of autophagosomes and subsequent autophagosome–lysosome fusion (Nguyen et al., 2016). The ATG4 family of cysteine proteases (ATG4A, -B, -C, and -D) cleaves ATG8 proteins immediately after a conserved glycine residue in their C terminus in a process dubbed “priming,” which leads to the formation of ATG8-I (Skytte Rasmussen et al., 2017; Tanida et al., 2004). ATG7 then attaches to the exposed glycine residue of ATG8-I via a thioester linkage to form an E1 ubiquitin-like complex that transfers ATG8-I to ATG3 in a similar way to generate an E2-like complex (Ichimura et al., 2000). The ATG5–ATG12–ATG16L1 complex then catalyzes the E3-like transfer of ATG8-I from ATG3 to phosphatidylethanolamine to form ATG8-II, which is the lipidated species that is incorporated into double membrane–bound compartments such as autophagosomes (Hanada et al., 2007). The lipidation of ATG8s and their recruitment to the phagophore are not essential for the formation of autophagosomes but are important for phagophore expansion, the selective capture of autophagic substrates, and autophagosome–lysosome fusion (Kirkin and Rogov, 2019; Nguyen et al., 2016). Intriguingly, ATG8 lipidation is multifaceted, as ATG8s can be alternatively lipidated with phosphatidylserine (instead of phosphatidylethanolamine) to enable their recruitment to single membrane–bound compartments during LC3-associated phagocytosis, influenza infection, and lysosomal dysfunction (Durgan et al., 2021).The discovery of ATG8ylationKey insights into ATG8ylation came from the observation that various ATG8s form high-molecular-weight species in cells following the expression of their primed forms that have their C-terminal glycine exposed (for example, LC3B-G), bypassing the need for cleavage by ATG4 (Agrotis et al., 2019; Nguyen et al., 2021). Indeed, on an immunoblot, ATG8⁺ “smears” resemble that of ubiquitinated proteins (Agrotis et al., 2019; Nguyen et al., 2021). Traditionally, in the autophagy field, ATG8⁺ smears were thought to arise from poor antibody specificity. However, in light of recent findings, this widely accepted interpretation has been challenged, given that ATG8⁺ smears are enriched following ATG8 overexpression and disappear in the absence of ATG8s (Agrotis et al., 2019; Nguyen et al., 2021). Smearing has also been detected after immunoprecipitation of epitope-tagged ATG8s from cell extracts under denaturing conditions, ruling out noncovalent interactions accounting for this upshift (Agrotis et al., 2019; Nguyen et al., 2021). Further, smearing is not abolished by deubiquitinase treatment, arguing strongly against ATG8 ubiquitination as the cause (Nguyen et al., 2021). Everything considered, the most plausible explanation is that ATG8 itself undergoes covalent linkage to cellular proteins, akin to ubiquitin and NEDD8 modifiers, which are structurally similar to ATG8s. Remarkably, the protease ATG4 antagonizes the ATG8ylation state of many proteins (Agrotis et al., 2019; Nguyen et al., 2021).ATG4 displays isoform-specific proteolytic cleavage of ATG8ATG4 is required for the formation of autophagosomes, but its protease activity is not (Nguyen et al., 2021). The protease activity of ATG4 is, however, required for ATG8 processing, such as priming ahead of lipidation and de-lipidation, which removes excess ATG8 from autophagosomes and other membranes (Nguyen et al., 2021; Tanida et al., 2004; Fig. 1 A). Apart from these functions, ATG4 regulates the deubiquitinase-like removal of ATG8 from cellular proteins (de-ATG8ylation; Agrotis et al., 2019; Nguyen et al., 2021; Fig. 1 A). Consistent with this role, deletion of all four ATG4 isoforms (A, B, C, and D) increases the abundance of ATG8ylated proteins (Nguyen et al., 2021). In contrast, overexpression of ATG4B has the opposite effect, but only if its protease activity is intact (Agrotis et al., 2019). As such, ATG4 inhibits the ATG8ylation state of many proteins, which is likely to modulate their downstream functions.Open in a separate windowFigure 1.The many roles of ATG4 in ATG8 processing. (A) Molecular processing of ATG8 proteins by ATG4 illustrating its roles in priming, de-lipidation, and de-ATG8ylation. The structure of LC3B (Protein Data Bank accession no. 1V49) was used to denote ATG8 (G, glycine; PE, phosphatidylethanolamine). (B) Heatmap summarizing relationships between ATG4 isoforms and ATG8 family members. Data were summarized for qualitative interpretation (Agrotis et al., 2019; Li et al., 2011; Nguyen et al., 2021). Int., intermediate; N.d., not determined. (C) Graphical summary of questions moving forward with ATG8ylation (P, phosphorylation).ATG4 is an important “gatekeeper” for ATG8 conjugation events. ATG4 primes ATG8s to expose their C-terminal glycine, which is required for conjugation to proteins or lipids; however, ATG4 also catalyzes de-ATG8ylation and de-lipidation events, respectively (Agrotis et al., 2019; Nguyen et al., 2021; Tanida et al., 2004). Because the C-terminal glycine of a single ATG8 is occupied when conjugated to a protein or lipid, it is unlikely that ATG8ylated proteins directly engage with phagophore membranes in the same way as ATG8-II. Indeed, protease protection assays with recombinant ATG4B reveal that de-ATG8ylation of cell lysates remains unchanged with or without organellar membrane disruption, suggesting that ATG8ylated proteins are largely cytoplasmic facing rather than intraluminal (Agrotis et al., 2019). Paradoxically, however, ATG8ylation is enhanced by lysosomal V-type ATPase inhibition, which blocks the degradation of lysosomal contents, indicating that ATG8ylated substrates may undergo lysosome-dependent turnover (Agrotis et al., 2019; Nguyen et al., 2021). One explanation for these differences may be that the process of ATG8ylation is itself sensitive to lysosomal dysfunction.Functional relationships between ATG4s and ATG8sIsoforms of ATG4 show clear preferences for proteolytically processing ATG8 subfamilies (i.e., LC3s and GABARAPs) for de-ATG8ylation and priming upstream of phosphatidylethanolamine ligation (Agrotis et al., 2019; Li et al., 2011; Nguyen et al., 2021; Fig. 1 B). ATG4A strongly reduces the abundance of proteins that have been ATG8ylated with the GABARAP family while promoting ligation of GABARAPs to phosphatidylethanolamine (Agrotis et al., 2019; Nguyen et al., 2021; Fig. 1 B). In contrast, ATG4B strongly reduces the abundance of proteins that have been ATG8ylated with LC3 proteins while promoting ligation of LC3s to phosphatidylethanolamine (Agrotis et al., 2019; Nguyen et al., 2021; Fig. 1 B). In comparison, ATG4C and -D lack obvious de-ATG8ylation activity, although the latter weakly promotes phosphatidylethanolamine ligation to GABARAPL1 only (Nguyen et al., 2021). These functional similarities between ATG4 isoforms are consistent with both their sequence and structural homology (i.e., ATG4A and -B are most similar; Maruyama and Noda, 2018; Satoo et al., 2009). Structurally, ATG4B adopts an auto-inhibited conformation with its regulatory loop and N-terminal tail blocking substrate entry to its proteolytic core (Maruyama and Noda, 2018). LC3B induces conformational rearrangements in ATG4B that involve displacement of its regulatory loop and its N-terminal tail, with the latter achieved by an interaction between the ATG8-interacting region in its N-terminal tail with a second copy of LC3B that functions allosterically (Maruyama and Noda, 2018; Satoo et al., 2009). These rearrangements permit entry of LC3B into the proteolytic core of ATG4B, where cleavage of LC3B following its C-terminal glycine occurs (Li et al., 2011; Maruyama and Noda, 2018). ATG4B^L232 is directly involved in LC3B binding and its selectivity for LC3s (Satoo et al., 2009). This residue corresponds to ATG4A^I233 and, when substituted for leucine, gives ATG4A^I233L the ability to efficiently process LC3 proteins, whereas without this mutation it preferentially processes GABARAPs (Satoo et al., 2009). Moreover, the ATG8–ATG4 interaction is necessary for the de-ATG8ylation of cellular proteins, as an LC3B-G^Q116P mutant that cannot bind to ATG4 leads to widespread ATG8ylation (Agrotis et al., 2019). Altogether, these observations hint toward a common mechanism of ATG8 cleavage that regulates priming, de-lipidation, and de-ATG8ylation.Mitochondrial damage promotes ATG8ylationATG8ylation of cellular proteins appears to be enhanced by mitochondrial depolarization and inhibition of the lysosomal V-type ATPase (Agrotis et al., 2019; Nguyen et al., 2021). This may be the consequence of acute ATG4A and -B inhibition, given that cells lacking all ATG4 isoforms display an increased abundance of ATG8ylated proteins and are insensitive to further increase by mitochondrial depolarization or lysosomal V-type ATPase inhibition (Agrotis et al., 2019; Nguyen et al., 2021). Indeed, mitochondrial depolarization leads to activation of ULK1, which phosphorylates ATG4B^S316 to inhibit its protease activity (Pengo et al., 2017). Similarly, mitochondrial depolarization stimulates TBK1 activation, which prevents de-lipidation of ATG8s by blocking the ATG8–ATG4 interaction through phosphorylation of LC3C^S93/S96 and GABARAP-L2^S87/S88 (Herhaus et al., 2020; Richter et al., 2016). As such, ATG8 phosphorylation may render ATG8ylated substrates more resistant to de-ATG8ylation by ATG4s. This may be analogous to how chains of phosphorylated ubiquitin^S65 are more resistant to hydrolysis by deubiquitinating enzymes than unphosphorylated ones (Wauer et al., 2015). Moreover, ATG8ylation is insensitive to nutrient deprivation and pharmacological inhibition of mTOR, which rules out a functional contribution of this process to starvation-induced autophagy (Agrotis et al., 2019). Therefore, ATG8ylation may be a unique aspect of mitophagy (and perhaps also other forms of selective autophagy) given that depolarization potently activates Parkin-dependent mitophagy (Agrotis et al., 2019; Nguyen et al., 2021).Substrates of ATG8ylationBased on ATG8⁺ smearing, ATG4 regulates the de-ATG8ylation of numerous proteins (Agrotis et al., 2019; Nguyen et al., 2021). For the majority, their identity, induced structural and functional changes, and the cellular contexts during which these modifications occur await exploration. Considering that the ATG8 interactome is well characterized, it is likely that at least some ATG8ylated proteins have been mistaken for ATG8-binding partners (Behrends et al., 2010). Given their E2- and E3-like roles in ATG8 lipidation, it is remarkable that ATG3 and ATG16L1 are themselves modified by ATG8ylation (Agrotis et al., 2019; Hanada et al., 2007; Ichimura et al., 2000; Nguyen et al., 2021). Lysine mutagenesis indicates that ATG3^K243 is the “acceptor” site for ATG8ylation (Agrotis et al., 2019). ATG3^K243 is essential for its conjugation to either LC3B or ATG12 and is required for autophagosomes to form around damaged mitochondria (Agrotis et al., 2019; Radoshevich et al., 2010). This also raises the possibility that key functions originally attributed to ATG3–ATG12 conjugation may be, at least in part, due to ATG3–ATG8 conjugation. Because multiple high-molecular-weight species of ATG3 are enriched following immunoprecipitation of primed LC3B-G from cells lacking ATG4B, it is likely that ATG3 is either mono-ATG8ylated at several sites or poly-ATG8ylated (Agrotis et al., 2019). ATG8ylation of ATG3 may also reflect the stabilization of its E2-like intermediate (Ichimura et al., 2000). ATG8ylation of ATG16L1 may regulate whether canonical or noncanonical autophagy pathways are activated (Durgan et al., 2021; Nguyen et al., 2021). In line with this possibility, the WD40 domain mutant of ATG16L1^K490A prevents lipidation of ATG8s with phosphatidylserine (i.e., during noncanonical autophagy pathways) but not phosphatidylethanolamine (i.e., during canonical autophagy; Durgan et al., 2021). Moreover, given that ATG8ylation of protein targets correlates with the activation of mitophagy, it is tempting to speculate that it may stimulate the E2-/E3-like activity of the ATG8 conjugation machinery to amplify mitochondrial capture and destruction.Concluding remarksThe finding that numerous cellular proteins are modified by ATG8ylation poses several questions about how signaling networks are coordinated during selective autophagy (i.e., mitophagy). Whether ATG8ylation is augmented by mitochondrial injury per se or is the consequence of mitophagy activation is yet to be determined, as is whether this phenomenon occurs during other types of selective autophagy (e.g., ER-phagy, ribophagy, and lysophagy; Kirkin and Rogov, 2019; Fig. 1 C). While the in vivo relevance of ATG8ylation is not yet understood, it is plausible that this process could be altered in diseases with defective mitophagy (e.g., Parkinson’s disease and atherosclerosis). Exploring the mechanistic aspects of ATG8ylation (e.g., ATG8 ligases and regulatory proteins, linkage types, acceptor sites, etc.) and de-ATG8ylation by ATG4 will improve our understanding about how this modifier alters the structure and biological function of cellular proteins (Fig. 1 C). By identifying ATG8ylated substrates, or the ATG8ylome, insights into whether ATG8ylation is a ubiquitous epiphenomenon or a post-translational modification that is selective to proteins of distinct biological function(s) will become clearer (Fig. 1 C). Considering the similarity of ATG8s with bona fide modifier proteins (e.g., ubiquitin and ubiquitin-like proteins) and the diversity of their substrates (e.g., lipid species and proteins), only now are we beginning to understand the functional complexities of the ATG8 protein family.     

Computational Identification of Potential Molecular Interactions in Arabidopsis

Knowledge of the protein interaction network is useful to assist molecular mechanism studies. Several major repositories have been established to collect and organize reported protein interactions. Many interactions have been reported in several model organisms, yet a very limited number of plant interactions can thus far be found in these major databases. Computational identification of potential plant interactions, therefore, is desired to facilitate relevant research. In this work, we constructed a support vector machine model to predict potential Arabidopsis (Arabidopsis thaliana) protein interactions based on a variety of indirect evidence. In a 100-iteration bootstrap evaluation, the confidence of our predicted interactions was estimated to be 48.67%, and these interactions were expected to cover 29.02% of the entire interactome. The sensitivity of our model was validated with an independent evaluation data set consisting of newly reported interactions that did not overlap with the examples used in model training and testing. Results showed that our model successfully recognized 28.91% of the new interactions, similar to its expected sensitivity (29.02%). Applying this model to all possible Arabidopsis protein pairs resulted in 224,206 potential interactions, which is the largest and most accurate set of predicted Arabidopsis interactions at present. In order to facilitate the use of our results, we present the Predicted Arabidopsis Interactome Resource, with detailed annotations and more specific per interaction confidence measurements. This database and related documents are freely accessible at http://www.cls.zju.edu.cn/pair/.The complex cellular functions of an organism rely on physical interactions between proteins. Deciphering the protein-protein interaction network to understand higher level phenotypes and their regulations is always a major focus of both experimental biologists and computational biologists. A number of high-throughput (HTP) assays have been developed to identify in vitro protein interactions from several model organisms (Uetz et al., 2000; Giot et al., 2003; Li et al., 2004). A number of initiatives, such as IntAct (Kerrien et al., 2006), Molecular INTeraction database (Chatr-aryamontri et al., 2007), the Database of Interacting Proteins (Salwinski et al., 2004), Biomolecular Interaction Network Database (BIND; Alfarano et al., 2005), and BioGRID (Stark et al., 2006), have been established to systematically collect and organize the interaction data reported by both proteome-scale HTP experiments and traditional low-throughput studies focusing on individual proteins or pathways.Arabidopsis (Arabidopsis thaliana) has long been studied as a model organism to investigate the physiology, biochemistry, growth, development, and metabolism of a flowering plant at the molecular level. The molecular mechanism studies of various phenotypes and their regulations in Arabidopsis may be facilitated by a comprehensive reference protein interaction network, based on which working hypotheses could be invented with more guidance and confidence. However, due to technological limitations, most experimentally reported protein interactions in available databases were from other organisms. A very limited number of plant interactions could be found in these databases. Therefore, an accurate prediction of the Arabidopsis interactome would be valuable to assist relevant research.Studies on the computational identification of potential interactions started along with the advent of HTP interaction-detection technologies, which often produced a large number of false positives (Deane et al., 2002). Indirect evidence of protein interaction (e.g. protein colocalization and relevance in function) were hence introduced to boost the confidence of HTP results (Jansen et al., 2003). Further investigations demonstrated that direct inference of protein interactions from such indirect evidence alone was possible (Scott and Barton, 2007). The accuracy and effectiveness of using indirect evidence to predict interactions have also been thoroughly assessed (Qi et al., 2006; Suthram et al., 2006). These works offered precious insights into how protein interactions may be predicted accurately on a proteomic scale. In other organisms such as Homo sapiens, the prediction of an entire interactome has already been proven applicable and useful (Rhodes et al., 2005).On the other side, several efforts have been made to collect and organize a comprehensive map of Arabidopsis molecular interactions. For instances, around 20,000 interactions were inferred by homology to known interactions in other organisms (Geisler-Lee et al., 2007). Another work predicted 23,396 interactions based on multiple indirect data and curated 4,666 interactions from the literature and enzyme complexes (Cui et al., 2008). The Arabidopsis reactome database was established describing the functions of 2,195 proteins with 8,269 reactions in 318 superpathways (Tsesmetzis et al., 2008). And a general interaction database, IntAct (Kerrien et al., 2006), had allocated a special unit actively curating all plant protein interactions from literature and submitted data sets, which now contains 2,649 Arabidopsis interactions. However, in yeast, approximately 18,000 protein-protein interactions had been estimated for approximately 6,000 genes (Yu et al., 2008). Assuming the same rate of interaction, approximately 200,000 protein interactions would be expected for approximately 20,000 Arabidopsis genes. Therefore, the current collection of Arabidopsis interactions is still significantly limited. Moreover, most previous prediction works did not provide rigorous confidence measurements for their predicted interactions, which further limited their scope of applications.Recent advances in statistical learning presented a powerful algorithm, support vector machine (SVM), which may be used to predict interactions based on multiple indirect data. Although the basis of SVM had been laid in the 1960s, the idea of SVM was only officially proposed in the 1990s by Vapnik (1998, 2000). Then, research on its theoretical and application aspects thrived. It has been applied in a wide range of problems, including text categorization (de Vel et al., 2001; Kim et al., 2001), image classification and object detection (Ben-Yacoub et al., 1999; Karlsen et al., 2000), flood stage forecasting (Liong and Sivapragasam, 2002), microarray gene expression data analysis (Brown et al., 2000), drug design (Zhao et al., 2006a, 2006b), protein solvent accessibility prediction (Yuan et al., 2002), and protein fold prediction (Ding and Dubchak, 2001; Hua and Sun, 2001). Many studies have demonstrated that SVM was consistently superior to other supervised learning methods (Brown et al., 2000; Burbidge et al., 2001; Cai et al., 2003).In this work, with careful preparation of example data and selection of indirect evidence, we constructed an SVM model to predict potential Arabidopsis interactions. False positives were tightly controlled. With the high-confidence model, we identified altogether 224,206 potential interactions, which were expected to be 48.67% accurate and to cover 29.02% of the entire Arabidopsis interactome. More specific confidence measurements were also assigned on a per interaction basis. To facilitate the use of our results, we present the Predicted Arabidopsis Interactome Resource (PAIR; http://www.cls.zju.edu.cn/pair/), featuring detailed annotations and a friendly user interface.     

The molecular evolution of function in the CFTR chloride channel

The ATP-binding cassette (ABC) transporter superfamily includes many proteins of clinical relevance, with genes expressed in all domains of life. Although most members use the energy of ATP binding and hydrolysis to accomplish the active import or export of various substrates across membranes, the cystic fibrosis transmembrane conductance regulator (CFTR) is the only known animal ABC transporter that functions primarily as an ion channel. Defects in CFTR, which is closely related to ABCC subfamily members that bear function as bona fide transporters, underlie the lethal genetic disease cystic fibrosis. This article seeks to integrate structural, functional, and genomic data to begin to answer the critical question of how the function of CFTR evolved to exhibit regulated channel activity. We highlight several examples wherein preexisting features in ABCC transporters were functionally leveraged as is, or altered by molecular evolution, to ultimately support channel function. This includes features that may underlie (1) construction of an anionic channel pore from an anionic substrate transport pathway, (2) establishment and tuning of phosphoregulation, and (3) optimization of channel function by specialized ligand–channel interactions. We also discuss how divergence and conservation may help elucidate the pharmacology of important CFTR modulators.

IntroductionThe ATP-binding cassette (ABC) transporter superfamily includes many members of clinical relevance, such as the multidrug resistance proteins (MRPs) and other proteins involved in generation of antibiotic resistance, transport of a wide variety of substrates in pathogenic bacteria, and transport of bile acids, lipids, and lipopolysaccharides (Ford and Beis, 2019; Jetter and Kullak-Ublick, 2020). ABC transporter genes encode the largest family of transmembrane (TM) proteins among living organisms (Briz et al., 2019) and are expressed in all domains of life (Ford and Beis, 2019; Holland et al., 2003). Either function or dysfunction of ABC transporters is implicated in development or treatment of cancer (Briz et al., 2019; Nobili et al., 2020), neurological disorders (Jha et al., 2019; Sumirtanurdin et al., 2019), detoxification (Briz et al., 2019), visual function (Garces et al., 2018), and, among many other clinical presentations (Moitra and Dean, 2011), in cystic fibrosis (CF; Riordan et al., 1989). In CF, mutations in the gene encoding CFTR lead to loss of anion transport in a wide variety of epithelial tissues (Csanády et al., 2019). In this review, we use the data generated from >30 yr of intensive structure-function study of CFTR and related proteins to propose and evaluate a potential route by which CFTR may have evolved unique function as a phosphorylation-regulated chloride channel. New insights are made possible by the advent of high-resolution cryo-EM structures of CFTR and the recent cloning and characterization of the evolutionarily oldest known orthologue of CFTR, from sea lamprey (Lp-CFTR; see below), which exhibits many functional differences from the human CFTR orthologue (hCFTR; Cui et al., 2019a).Overview of CFTRCFTR is a Cl⁻/HCO₃⁻ channel whose dysfunction directly leads to CF, the most common life-shortening genetic disease among Caucasians, affecting ∼80,000 individuals worldwide (Riordan et al., 1989; https://cftr2.org/mutations_history). The role of CFTR has been well characterized in airway, intestine, and sweat gland epithelial cells (Buchwald et al., 1991; Gonska et al., 2009; Haq et al., 2016; Quinton et al., 2012; Quinton, 2007; Trezíse and Buchwald, 1991), where the anionic flux mediated by the protein contributes to water secretion and regulation of pH (Pezzulo et al., 2012; Rowe et al., 2014). CFTR also functions in several nonepithelial cell types (Cook et al., 2016; Edlund et al., 2014; Gao and Su, 2015; Guo et al., 2014; Norez et al., 2014; Pohl et al., 2014; Schulz and Tümmler, 2016; Su et al., 2011), including in the brain (Ballerini et al., 2002; Guo et al., 2009; Hincke et al., 1995; Johannesson et al., 1997; Mulberg et al., 1995; Mulberg et al., 1998; Parkerson and Sontheimer, 2004; Pfister et al., 2015; Plog et al., 2010; Weyler et al., 1999). Several hundred disease-causing mutations have been identified in the CFTR gene. For a subset of these mutations, four small-molecule modulator therapeutics from Vertex Pharmaceuticals, Inc. that increase the surface expression or activity of CFTR have been approved for clinical use. The first approved drug, VX-770 (ivacaftor), is a gating potentiator that increases function of certain CFTR mutants (Cui et al., 2019b; Sosnay et al., 2013; Van Goor et al., 2009; Van Goor et al., 2014; Yu et al., 2012). A better understanding of these drugs and their binding sites may aid in refining the next class of therapeutics.ABC transporters use the energy of ATP binding and hydrolysis to accomplish the active import or export of various substrates across membranes (Rees et al., 2009). There are seven subfamilies of mammalian ABC transporters (ABCA, ABCB, ABCC,… ABCG), of which the E and F subfamilies do not bear actual transport function (Dean et al., 2001; Ford and Beis, 2019). A new classification of the ABC transporter superfamily that is based on the transmembrane domain (TMD) fold has recently been suggested (Thomas et al., 2020). CFTR is denoted ABCC7 and a member of type IV, respectively, according to these two classification schemes. CFTR bears ATPase activity like that of other ABCC subfamily members (Li et al., 1996; Stratford et al., 2007; Jordan et al., 2008), but biophysical methods have firmly established that CFTR functions as a phosphorylation-activated and ATP-gated ion channel (Anderson et al., 1991a; Anderson et al., 1991b; Bear et al., 1992; Berger et al., 1991; Sheppard et al., 1993), whereas its closest ABCC relatives function as multispecific exporters of organic anions (Jordan et al., 2008). CFTR may directly mediate the flux of glutathione (Gao et al., 1999; Kogan et al., 2003; Linsdell and Hanrahan, 1998), although CFTR-mediated active transport has not been shown, to our knowledge. Glutathione is transported by close ABCC relatives ABCC1/MRP1 (Mao et al., 1999) and ABCC4/MRP4 (Choi et al., 2001; Ko et al., 2002; Kogan et al., 2003; Ritter et al., 2005; Serrano et al., 2006); previous analysis has identified ABCC4 as CFTR’s closest relative (Jordan et al., 2008; see also Cui et al., 2019a). The domain organization of CFTR is similar to that of its closest relatives, the “short transporters” of the ABCC subfamily (Jordan et al., 2008; Ford and Beis, 2019; Srikant and Gaudet, 2019), with two nucleotide-binding domains (NBDs) that function in ATP binding and hydrolysis, and two TMDs, each containing six TM helices that comprise the substrate transport pathway (Fig. 1). However, unique to CFTR is an intracellular regulatory (R) domain that contains multiple consensus sites for phosphorylation by PKA (Sebastian et al., 2013).Open in a separate windowFigure 1.Domain architecture of CFTR. (A) Five functional domains: TMD1, NBD1, R domain with multiple phosphorylation sites, TMD2, and NBD2. Each TMD includes six transmembrane helices, numbered 1–12. The N-terminus includes the lasso motif (shown in pink), whereas the C-terminus includes a PDZ binding domain motif (yellow). (B) hCFTR from cryo-EM structure (PDB accession no. 6MSM). The R domain is not shown, because it is intrinsically unstructured.The opening of CFTR may be simplified to involve three sequential steps that have been uncovered via a combination of functional and structural data. First, PKA binds to (Mihályi et al., 2020) and phosphorylates (Rich et al., 1991) the aforementioned R domain, which results in loss of inhibitory interactions between that domain and the rest of the channel protein. Second, ATP binds to two sites at the interface of the cytoplasmic NBDs, which promotes a stable NBD dimer (Mense et al., 2006; Vergani et al., 2005). Finally, the wave of conformational changes associated with ATP-induced dimerization of the NBDs is transmitted to the pore domain, resulting in pore opening (Rahman et al., 2013; Simhaev et al., 2017; Sorum et al., 2015; Strickland et al., 2019). In related ABC exporters, ATP-dependent dimerization of the NBDs drives an overall transition from inward- to outward-facing conformation of the TMDs; this function was coopted by CFTR to drive ATP-induced channel opening (Fig. 2). At the level of individual residues, there is high conservation with transporters among amino acids in CFTR that are proposed to stabilize the inward-facing (closed) conformation in the absence of ATP (Wang et al., 2010; Wei et al., 2014; Wei et al., 2016), suggesting conservation of motifs integral to energetic signaling (Wang et al., 2014b; Wei et al., 2014; Wei et al., 2016). The close proximity of intracellular loops 2 and 4 (ICL2 and ICL4, respectively; Doshi et al., 2013; Wang et al., 2014b), constriction of the intracellular vestibule (Bai et al., 2011), and dilation of the extracellular vestibule, relative to the closed state, are all associated with channel opening (Beck et al., 2008; Infield et al., 2016; Norimatsu et al., 2012b; Rahman et al., 2013; Strickland et al., 2019). The CFTR pore opens in stages, requiring the sequential breaking and forming of intraprotein residue–residue interactions (Cui et al., 2013, 2014; Rahman et al., 2013), resulting in two subconductance states in addition to the full-conductance state (Gunderson and Kopito, 1995; Zhang et al., 2005a; Zhang et al., 2005b; Fig. 3). Using a particularly informative cysteine mutant at the outer vestibule, R334C-CFTR, the McCarty laboratory found that transitions between these subconductance states are highly dependent upon experimental conditions; for example, closing transitions almost always start from the s2 state in the presence of ATP, and transitions from s2 to f never occur in channels bound with the poorly hydrolyzable ATP analogue AMP-PNP (see also Langron et al., 2018), suggesting that this transition requires hydrolysis of nucleotide at the NBDs (Zhang et al., 2005a; Zhang et al., 2005b). Subconductance states are evident in recordings of WT CFTR from membrane patches and planar lipid bilayers, depending on experimental conditions, indicating that these represent inherent steps in gating of the channel pore (Gunderson and Kopito, 1995). In WT-hCFTR, this open pore is quite stable and does not close until ATP is hydrolyzed at the NBDs (Baukrowitz et al., 1994). Note that because CFTR displays three types of gating in one channel (phosphorylation-mediated, ligand-mediated, and pore-mediated gating), it serves as an exemplary target for studying the evolution of functional mechanisms within a single membrane protein.Open in a separate windowFigure 2.Hypothesis for emergence of channel function in CFTR. Modification of ATP-dependent transport activity in ABC transporters led to channel behavior, coopting the conformational changes necessary for unidirectional substrate transport in common ABC transporter systems. CFTR evolved features that break the alternating access cycle (solid-line arrows), enabling it to be open at both ends (box). Color scheme for major domains (again, lacking the R domain) is the same as in Fig. 1.Open in a separate windowFigure 3.Gating scheme for CFTR. Prephosphorylated channels are shown in the membrane (gray slab) with two TMDs (brown and dark blue) and two NBDs (green and light blue), with ATP (red circle) and ADP (yellow circle). ATP-dependent gating is shown as including NBD-mediated gating steps leading to pore gating between conductance levels. Here, we do not distinguish between s1 and s2 subconductance levels, because s1→s2 occurs very rapidly in WT-hCFTR.Natural history of the CFTR channel in vertebratesGiven the structural conservation among CFTR and ABC exporters noted above, and functional conservation in terms of ATP dependence, how CFTR evolved to function as an anion channel regulating passive ionic diffusion has been an enduring question (Srikant, 2020; Srikant et al., 2020). Molecular evolution studies are facilitated by the availability of many orthologues for the protein/gene of interest, spanning as much of the evolutionary record as possible. Currently, ∼300 CFTR orthologues are included in GenBank/UniProt, although not all of these are represented by expressible cDNA clones. Until very recently, the oldest CFTR orthologue known was from the dogfish shark, arising ∼150 million yr ago (MYA; Fig. 4; Marshall et al., 1991); this orthologue bears functional characteristics similar to those of hCFTR. However, reasoning that the identification of an earlier CFTR orthologue with altered structure/function would provide novel insight into the evolution of epithelial anion transport, the Gaggar and McCarty laboratories recently led an effort to clone and characterize the Lp-CFTR (Cui et al., 2019a), which arose ∼550 MYA (Smith et al., 2013). The identification of a CFTR orthologue in the jawless vertebrates establishes that CFTR exists across all vertebrates, predating the divergence of jawed and jawless vertebrates at the end of the Cambrian Period ∼488 MYA. Sequence analysis indicates 46% sequence identity and 65% sequence similarity between Lp-CFTR and hCFTR, which is much lower than that among jawed vertebrate CFTRs (jv-CFTRs) and includes surprising divergence in functionally relevant motifs. Accordingly, Lp-CFTR differs from hCFTR in multiple functional characteristics (Fig. 4). Thus, it cannot be automatically assumed that every position in CFTR that is unique in sea lamprey represents transitional change in the development of regulated channel activity. A good example in this regard is that of F508 in hCFTR, which is conserved across multiple ABC proteins but is leucine in lamprey (Cui et al., 2019a). Sorum et al. (2017) showed that replacing F508 with L in hCFTR significantly reduced its open probability. All known CFTRs other than Lp-CFTR and all known human ABCCs have F at this position, where the aromatic side chain is necessary for stabilizing the outward-facing state (Cui et al., 2006), so finding that this is substituted by a nonaromatic side chain in Lp-CFTR is mechanistically interesting and may represent a species-specific adaptation (Cui et al., 2019a).Open in a separate windowFigure 4.Simplified and truncated evolutionary tree for vertebrates. Green, common vertebrate ancestor; blue, jawless vertebrates; red and yellow, jawed vertebrates; yellow, mammals. CFTR orthologues studied in functional assays are shown underlined. (The time domain in this figure is not implied.)Table 1.Comparison of features between human and lamprey orthologues, focusing on three major domains of function: channel behavior, regulation, and modulation

The spatial and temporal repeatability of PHA-responses

   INTRODUCTION   The capacity to mount a cell-mediated immune response in birdsis often quantified as the swelling following an injection ofphytohaemagglutinin (PHA) into the wing-web. Most studies havefound the repeatability of consecutive measurements of the sameswelling to be high (e.g., Alonso-Alvarez and Tella, 2001; Fargalloet al., 2002; Saino et al., 1997; Smits et al., 1999; Tellaet al., 2000). However, as pointed out by Siva-Jothy and Ryder(2001), repeatability calculated this way only estimates theprecision with which an experimenter measures the size of aparticular swelling; it does not encompass other componentsof measurement error. Furthermore, such estimates of repeatabilitydo not capture temporal variation in individuals' PHA-responses.To our knowledge, no study has reported the latter types